Impacts of Aggregation Methods and Trophospecies Number on the Structure and Function of Marine Food Webs

Aggregation of species with similar ecological properties is one of the effective methods to simplify food web researches.However,species aggregation will affect not only the complexity of modeling process but also the accuracy of models’outputs.Selection of aggregation methods and the number of trophospecies are the keys to study the simplification of food web.In this study,three aggregation methods,including taxonomic aggregation(TA),structural equivalence aggregation(SEA),and self-organizing maps(SOM),were analyzed and compared with the linear inverse model–Markov Chain Monte Carlo(LIM-MCMC)model.Impacts of aggregation methods and trophospecies number on food webs were evaluated based on the robustness and unitless of ecological net-work indices.Results showed that aggregation method of SEA performed better than the other two methods in estimating food web structure and function indices.The effects of aggregation methods were driven by the differences in species aggregation principles,which will alter food web structure and function through the redistribution of energy flow.According to the results of mean absolute percentage error(MAPE)which can be applied to evaluate the accuracy of the model,we found that MAPE in food web indices will increase with the reducing trophospecies number,and MAPE in food web function indices were smaller and more stable than those in food web structure indices.Therefore,trade-off between simplifying food webs and reflecting the status of ecosystem should be con-sidered in food web studies.These findings highlight the importance of aggregation methods and trophospecies number in the analy-sis of food web simplification.This study provided a framework to explore the extent to which food web models are affected by dif-ferent species aggregation,and will provide scientific basis for the construction of food webs.

Prediction Model-based Multi-objective Optimization for Mix-ratio Design of Recycled Aggregate Concrete

The prediction model for mechanical properties of RAC was established through the Bayesian optimization-based Gaussian process regression(BO-GPR)method,where the input variables in BO-GPR model depend on the mix ratio of concrete.Then the compressive strength prediction model,the material cost,and environmental factors were simultaneously considered as objectives,while a multi-objective gray wolf optimization algorithm was developed for finding the optimal mix ratio.A total of 730 RAC datasets were used for training and testing the predication model,while the optimal design method for mix ratio was verified through RAC experiments.The experimental results show that the predicted,testing,and expected compressive strengths are nearly consistent,illustrating the effectiveness of the proposed method.

Cyber-physical Modeling Technique based Dynamic Aggregation of Wind Farm Considering LVRT Characteristic

With the increasing penetration of wind power,large-scale integrated wind turbine brings stability and security risks to the power grid.For the aggregated modeling of large wind farms,it is crucial to consider low voltage ride-through(LVRT)characteristics.However,in aggregation methods,the approximate neglect behavior is essential,which leads to inevitable errors in the aggregation process.Moreover,the lack of parameters in practice brings new challenges to the modeling of a wind farm.To address these issues,a novel cyber-physical modeling method is proposed.This method not only overcomes the aggregation problem under the black-box wind farm but also accurately realizes the aggregation error fitting according to the operation data.The simulation results reveal that the proposed method can accurately simulate the dynamic behaviors of the wind farm in various scenarios,whether in LVRT mode or normal mode.

Simulation research on monomer agglomeration of nonmetallic inclusions in steel with a diffusion limited aggregation model

The monomer agglomeration of nonmetallic inclusions was simulated with a diffusion limited aggregation （DLA） model of the fractal theory. The simulation study with a random two-dimensional diffusion was carried out. The results indicate that the DLA model can be used for the simulation of agglomeration behavior of the cluster-type inclusions. The morphology of clusters was observed with SEM and compared with the simulated agglomerates. The modelling procedure of the DLA model is applicable for the agglomeration process. The uncertainty of agglomeration process and the persuasive average agglomerative ratio was analyzed. The factors about the agglomerative ratio with the collision path distance and the size of particles or seed were discussed. The adherence of the nonmetallic inclusions on the dam, the weir and the walls of a tundish, and the absorption of inclusions by stopper or nozzle were also discussed.

Investigation of molecular aggregation mechanism of glipizide/cyclodextrin complexation by combined experimental and molecular modeling approaches

Cyclodextrin complexation is a wise strategy to enhance aqueous solubility of waterinsoluble drugs.However,the aggregation mechanism of drug-cyclodextrin complexes is still unclear.This research aimed to investigate the molecular aggregation mechanism of glipizide/cyclodextrin complexation by the combination of experimental and modeling methods.Binding free energies between glipizide and cyclodextrins from modeling calculations were higher than those by the phase solubility diagram method.Both experimental and modeling results showed that methylated-β-cyclodextrin exhibited the best solubilizing capability to glipizide.Size-measurement results confirmed the aggregation between glipizide and all four cyclodextrins in high concentrations.Glipizide/γ-cyclodextrin and glipizide/β-cyclodextrin complexes showed stronger aggregation trend than HP-β-cyclodextrin and methylated-β-cyclodextrin.The substituted groups in the rim of HP-β-cyclodextrin and methylated-β-cyclodextrin lead to weak aggregation.This research provided us a clear molecular mechanism of glipizide/cyclodextrin complexation and aggregation.This research will also benefit the formulation development of cyclodextrin solubilization.

Simulation of Fracture Process of Lightweight Aggregate Concrete Based on Digital Image Processing Technology

The mechanical properties and failure mechanism of lightweight aggregate concrete(LWAC)is a hot topic in the engineering field,and the relationship between its microstructure and macroscopic mechanical properties is also a frontier research topic in the academic field.In this study,the image processing technology is used to establish a micro-structure model of lightweight aggregate concrete.Through the information extraction and processing of the section image of actual light aggregate concrete specimens,the mesostructural model of light aggregate concrete with real aggregate characteristics is established.The numerical simulation of uniaxial tensile test,uniaxial compression test and three-point bending test of lightweight aggregate concrete are carried out using a new finite element method-the base force element method respectively.Firstly,the image processing technology is used to produce beam specimens,uniaxial compression specimens and uniaxial tensile specimens of light aggregate concrete,which can better simulate the aggregate shape and random distribution of real light aggregate concrete.Secondly,the three-point bending test is numerically simulated.Thirdly,the uniaxial compression specimen generated by image processing technology is numerically simulated.Fourth,the uniaxial tensile specimen generated by image processing technology is numerically simulated.The mechanical behavior and damage mode of the specimen during loading were analyzed.The results of numerical simulation are compared and analyzed with those of relevant experiments.The feasibility and correctness of the micromodel established in this study for analyzing the micromechanics of lightweight aggregate concrete materials are verified.Image processing technology has a broad application prospect in the field of concrete mesoscopic damage analysis.

Non-Overlapping Conditions to Enable Multi- Dimensional Behavioral Models/DPDs for Multi-Band or Non-Continuous Carrier Aggregation Systems

To linearize the multi.band PAs/transmitters, a serial of multi.band predistortion models based on multi.dimensional architecture have been proposed. However, most of these models work properly only for the signals whose harmonic and intermodulation products of carriers' non.overlap with the interested fundamental bands. In this paper, the non.overlapping conditions for dual.band and tri.band signals are derived and denoted in the form of closed.form expression. It can be used to verify whether a given dual.band/multi.band signals can be linearized properly by these multi.dimensional behavioral models. Also the conditions can be used to plan the frequency spacing and maximum bandwidth of a multi.band or non.continuous carrier aggregation signal. Several dual.band and triband signals were tested on the same PA, by employing 2.D DPD and 3.D DPD behavioral models. The measurement results show that the signals which don't satisfy the non.overlapping conditions cannot be linearized well by the multi.dimensional behavioral models which does not take the harmonic and intermodulation products of carriers' into account.

Clustered Federated Learning with Weighted Model Aggregation for Imbalanced Data

As a promising edge learning framework in future 6G networks,federated learning(FL)faces a number of technical challenges due to the heterogeneous network environment and diversified user behaviors.Data imbalance is one of these challenges that can significantly degrade the learning efficiency.To deal with data imbalance issue,this work proposes a new learning framework,called clustered federated learning with weighted model aggregation(weighted CFL).Compared with traditional FL,our weighted CFL adaptively clusters the participating edge devices based on the cosine similarity of their local gradients at each training iteration,and then performs weighted per-cluster model aggregation.Therein,the similarity threshold for clustering is adaptive over iterations in response to the time-varying divergence of local gradients.Moreover,the weights for per-cluster model aggregation are adjusted according to the data balance feature so as to speed up the convergence rate.Experimental results show that the proposed weighted CFL achieves a faster model convergence rate and greater learning accuracy than benchmark methods under the imbalanced data scenario.

Four Types of Percolation Transitions in the Cluster Aggregation Network Model

We study the percolation transition in a one-species cluster aggregation network model, in which the parameter α describes the suppression on the cluster sizes. It is found that the model can exhibit four types of percolation transitions, two continuous percolation transitions and two discontinuous ones. Continuous and discontinuous percolation transitions can be distinguished from each other by the largest single jump. Two types of continuous percolation transitions show different behaviors in the time gap. Two types of discontinuous percolation transitions are different in the time evolution of the cluster size distribution. Moreover, we also find that the time gap may also be a measure to distinguish different discontinuous percolations in this model.

Discrete element modeling of migration and evolution rules of coarse aggregates in the static compaction process

To investigate migration and evolution rules of coarse aggregates in the static compaction process, an algorithm of generating digital coarse aggregates that can reflect real morphology（ such as shape, size and fracture surface） of aggregate particles, is represented by polyhedral particles based on the discrete element method（ DEM）. A digital specimen comprised of aggregates and air voids is developed. In addition,a static compaction model consisting of a digital specimen and three plates is constructed and a series of evaluation indices such as mean contact force σMCF, wall stress in direction of zcoordinate σWSZZ, porosity and coordination numbers are presented to investigate the motion rules of coarse aggregates at different compaction displacements of 7. 5, 15 and 30 mm. The three-dimensional static compaction model is also verified with laboratory measurements. The results indicate that the compaction displacements are positively related to σMCF and σWSZZ, which increase gradually with the increase in iterative steps. When the compaction proceeds, the digital specimen porosity decreases, but the coordination number increases. The variation ranges of these four indices are different at different compaction displacements. This study provides a method to analyze the compaction mechanism of particle materials such as asphalt mixture and graded broken stone.

Investigation into mechanisms and kinetics of asphaltene aggregation in toluene/n-hexane mixtures

Determining the rate of asphaltene particle growth is one of the main problems in modeling of asphaltene precipitation and deposition.In this paper,the kinetics of asphaltene aggregation under different precipitant concentrations have been studied.The image processing method was performed on the digital photographs that were taken by a microscope as a function of time to determine the asphaltene aggregation growth mechanisms.The results of image processing by MATLAB software revealed that the growth of asphaltene aggregates is strongly a function of time.Different regions could be recognized during asphaltene particle growth including reaction-and diffusion-limited aggregation followed by reaching the maximum asphaltene aggregate size and start of asphaltene settling and the final equilibrium.Modeling has been carried out to predict the growth of asphaltene particle size based on the fractal theory.General equations have been developed for kinetics of asphaltene aggregation for reaction-limited aggregation and diffusion-limited aggregation.The maximum size of asphaltene aggregates and settling time were modeled by using force balance,acting on asphaltene particles.Results of modeling show a good agreement between laboratory measurements and model calculations.

Kinetic network models to elucidate aggregation dynamics of aggregation-induced emission systems

Aggregation-induced emission(AIE)is a phenomenon where a molecule that is weakly or non-luminescent in a diluted solution becomes highly emissive when aggregated.AIE luminogens(AIEgens)hold promise in diverse applications like bioimaging,chemical sensing,and optoelectronics.Investigation in AIE luminescence is also critical for understanding aggregation kinetics as the aggregation process is an essential component of AIE emission.Experimental investigation of AIEgen aggregation is challenging due to the fast timescale of the aggregation and the amorphous aggregate structures.Computer simulations such as molecular dynamics(MD)simulation provide a valuable approach to complement experiments with atomic-level knowledge to study the fast dynamics of aggregation processes.However,individual simulations still struggle to systematically elucidate heterogeneous kinetics of the formation of amorphous AIEgen aggregates.Kinetic network models(KNMs),constructed from an ensemble of MD simulations,hold great potential in addressing this challenge.In these models,dynamic processes are modeled as a series ofMarkovian transitions occurring among metastable conformational states at discrete time intervals.In this perspective article,we first review previous studies to characterize the AIEgen aggregation kinetics and their limitations.We then introduce KNMs as a promising approach to elucidate the complex kinetics of aggregations to address these limitations.More importantly,we discuss our perspective on linking the output of KNMs to experimental observations of time-resolved AIE luminescence.We expect that this approach can validate the computational predictions and provide great insights into the aggregation kinetics for AIEgen aggregates.These insights will facilitate the rational design of improved AIEgens in their applications in biology and materials sciences.

Growth and aggregation micromorphology of natural gas hydrate particles near gas-liquid interface under stirring condition

To investigate the morphological evolution of the whole growth and aggregation processes of hydrate crystals near the gas–liquid interface,we used a high-pressure visual reactor with high-speed camera to capture the micromorphology of hydrate particles in a natural gas+pure water system with pressure from 2.6 to 3.6 MPa and sub-cooling from 4.7 to 6.23C.The results showed that under low sub-cooling conditions,the amount and size of particles increased first and then decreased in the range of 0–330 lm,and the small particles always dominated.These particles can be roughly classified into two categories:planar flake particles and polyhedral solid particles.Then,the concept of maximum growth dominant particle size was proposed to distinguish the morphological boundary of growth and aggregation.In addition,the micro model was established to better reflect the effects of particle formation process and evolution mechanism near the gas–liquid interface under stirring condition.The results of this study can provide a guidance for flow assurance in multiphase pipeline.

Aggregate gradation design of asphalt mixture with stone-to-stone contact based on fuller's model

Based on Fuller＇s model, a gradation design is presented for the load-carrying capacity of an asphalt mixture with stone-to-stone contact. The coarse aggregate gradation, fine aggregate and filler gradation are respectively designed for their different effects on an asphalt mixture with stone-to-stone contact. The equation of coarse aggregate gradation is deduced from the Fuller＇s model. Fine aggregate gradation is calculated by using Fuller＇s equation. The asphalt mixture with the 16 mm maximum size of aggregate is verified. When the coefficient of coarse aggregate gradation is 0.35 and fine aggregate gradation is 0.25, the volume parameters of asphalt mixture meet the technical specifications. Moreover, the high temperature stability and crack resistance at low temperature are all well.

CONSERVATIVE ESTIMATING FUNCTION IN THE NONLINEAR REGRESSION MODEL WITH AGGREGATED DATA

The purpose of this paper is to study the theory of conservative estimating functions in nonlinear regression model with aggregated data. In this model, a quasi-score function with aggregated data is defined. When this function happens to be conservative, it is projection of the true score function onto a class of estimation functions. By constructing, the potential function for the projected score with aggregated data is obtained, which have some properties of log-likelihood function.

Mathematical models for properties of mortars with admixtures and recycled fine aggregates from demolished concretes

In order to expand the engineering application of recycle aggregate mortars （RAM） with aggregates from demolished concretes, the models for the properties of RAM and the replacement rate of these recycled fine aggregates were proposed. First, different kinds of mathematical models for the basic properties （compressive strength, water retention rate, and consistency loss） of RAM with two kinds of admixtures, thickening powders （TP） and self-made powdery admixtures （SSCT） designed for RAM, and the replacement rates were established, while the average relative errors and relative standard errors of these models were calculated. Additionally, the models and their error analyses for the curves of drying shrinkage and curing time of RAM ＋ SSCT at different replacement rates were put forward. The results show that polynomial functions should be used to calculate the basic properties of RAM ＋ TP and RAM ＋ SSCT at different replacement rates. In addition, polynonfial functions are the most optimal models for the sharp shrinkage sections in the curves of drying shrinkage-curing time of RAM ＋ SSCT, while exponential functions should be used as the models for the slow shrinkage sections and steady shrinkage sections.

Aggregated morphodynamic modelling of tidal inlets and estuaries

Aggregation is used to represent the real world in a model at an appropriate level of abstraction.We used the convection-diffusion equation to examine the implications of aggregation progressing from a three-dimensional(3D)spatial description to a model representing a system as a single box that exchanges sediment with the adjacent environment.We highlight how all models depend on some forms of parametric closure,which need to be chosen to suit the scale of aggregation adopted in the model.All such models are therefore aggregated and make use of some empirical relationships to deal with sub-scale processes.One such appropriately aggregated model,the model for the aggregated scale morphological interaction between tidal basin and adjacent coast(ASMITA),is examined in more detail and used to illustrate the insight that this level of aggregation can bring to a problem by considering how tidal inlets and estuaries are impacted by sea level rise.

Physical Model of Drying Shrinkage of Recycled Aggregate Concrete

We prepared concretes（RC0, RC30, and RC100） with three different mixes. The poresize distribution parameters of RAC were examined by high-precision mercury intrusion method（MIM） and nuclear magnetic resonance（NMR） imaging. A capillary-bundle physical model with random-distribution pores（improved model, IM） was established according to the parameters, and dry-shrinkage strain values were calculated and verified. Results show that in all pore types, capillary pores, and gel pores have the greatest impacts on concrete shrinkage, especially for pores 2.5-50 and 50-100 nm in size. The median radii are 34.2, 31, and 34 nm for RC0, RC30, and RC100, respectively. Moreover, the internal micropore size distribution of RC0 differs from that of RC30 and RC100, and the pore descriptions of MIM and NMR are consistent both in theory and in practice. Compared with the traditional capillary-bundle model, the calculated results of IM have higher accuracy as demonstrated by experimental verifi cation.

A New 3D Meso-mechanical Modeling Method of Coral Aggregate Concrete Considering Interface Characteristics

On the basis of the three-dimensional(3D)random aggregate&mortar two-phase mesoscale finite element model,C++programming was used to identify the node position information of the interface between the aggregate and mortar elements.The nodes were discretized at this position and the zero-thickness cohesive elements were inserted.After that,the crack energy release rate fracture criterion based on the fracture mechanics theory was assigned to the failure criterion of the interface transition zone(ITZ)elements.Finally,the three-phase mesomechanical model based on the combined finite discrete element method(FDEM)was constructed.Based on this model,the meso-crack extension and macro-mechanical behaviour of coral aggregate concrete(CAC)under uniaxial compression were successfully simulated.The results demonstrated that the meso-mechanical model based on FDEM has excellent applicability to simulate the compressive properties of CAC.