Dynamic intelligent prediction approach for landslide displacement based on biological growth models and CNN-LSTM

Influenced by complex external factors,the displacement-time curve of reservoir landslides demonstrates both short-term and long-term diversity and dynamic complexity.It is difficult for existing methods,including Regression models and Neural network models,to perform multi-characteristic coupled displacement prediction because they fail to consider landslide creep characteristics.This paper integrates the creep characteristics of landslides with non-linear intelligent algorithms and proposes a dynamic intelligent landslide displacement prediction method based on a combination of the Biological Growth model(BG),Convolutional Neural Network(CNN),and Long ShortTerm Memory Network(LSTM).This prediction approach improves three different biological growth models,thereby effectively extracting landslide creep characteristic parameters.Simultaneously,it integrates external factors(rainfall and reservoir water level)to construct an internal and external comprehensive dataset for data augmentation,which is input into the improved CNN-LSTM model.Thereafter,harnessing the robust feature extraction capabilities and spatial translation invariance of CNN,the model autonomously captures short-term local fluctuation characteristics of landslide displacement,and combines LSTM's efficient handling of long-term nonlinear temporal data to improve prediction performance.An evaluation of the Liangshuijing landslide in the Three Gorges Reservoir Area indicates that BG-CNN-LSTM exhibits high prediction accuracy,excellent generalization capabilities when dealing with various types of landslides.The research provides an innovative approach to achieving the whole-process,realtime,high-precision displacement predictions for multicharacteristic coupled landslides.

Study and Modeling of Human Biological Tissue Exposed to High Frequency Electromagnetic Waves

The main objective of this proposed article is to provide explanations to justify the validity of the results of the studies of the interaction between the electromagnetic fields and the human body. It can also find direct applications in the characterization and modeling of the macroscopic electrical properties of the biological media for assessing the effects of fields induced by electromagnetic radiation sources in the human body to set up new standards on the Human exposure to electromagnetic fields. To do this, we have taken into account the different physical phenomena of propagation of a hyper-frequency electromagnetic plane wave and on the other hand, the experimental values in order to model the electrical behavior of human biological tissues based on an equivalent electronic circuit model composed of capacities, resistance and reel, which assimilates the biological tissues of the skin, grease, blood. This model using the characteristic impedance of the dielectric support makes it possible to evaluate the voltage induced by the electromagnetic waves of the hyper-frequencies in the studied biological system. The results of the simulations obtained from computer tools demonstrate that the hyper-frequency electromagnetic waves can result in an elevation of the electrical potential of the biological tissues. Despite this potential is a decreasing function of the penetration depth.

Analysis and FDTD Modeling of the Influences of Microwave Electromagnetic Waves on Human Biological Systems

The interactions of electromagnetic waves with the human body are complex and depend on several factors related to the characteristics of the incident wave, including its frequency, its intensity, the polarization of the tissue encountered, the geometry of the tissue and its electromagnetic properties. That’s to say, the dielectric permittivity, the conductivity and the type of coupling between the field and the exposed body. A biological system irradiated by an electromagnetic wave is traversed by induced currents of non-negligible density;the water molecules present in the biological tissues exposed to the electromagnetic field will begin to oscillate at the frequency of the incident wave, thus creating internal friction responsible for the heating of the irradiated tissues. This heating will be all the more important as the tissues are rich in water. This article presents the establishment from a mathematical and numerical analysis explaining the phenomena of interaction and consequences between electromagnetic waves and health. Since the total electric field in the biological system is unknown, that is why it can be determined by the Finite Difference Time Domain FDTD method to assess the electromagnetic power distribution in the biological system under study. For this purpose, the detailed on the mechanisms of interaction of microwave electromagnetic waves with the human body have been presented. Mathematical analysis using Maxwell’s equations as well as bio-heat equations is the basis of this study for a consistent result. Therefore, a thermal model of biological tissues based on an electrical analogy has been developed. By the principle of duality, an electrical model in the dielectric form of a multilayered human tissue was used in order to obtain a corresponding thermal model. This thermal model made it possible to evaluate the temperature profile of biological tissues during exposure to electromagnetic waves. The simulation results obtained from computer tools show that the temperature in the biological tissue is a linear function of the duration of exposure to microwave electromagnetic waves.

Permeability modeling of self-healing due to calcium carbonate precipitation in cement-based materials with mineral additives

The permeability modeling of self-healing due to calcium carbonate precipitation in cement-based materials with mineral additives was studied in this work. The parameters of calcium carbonate precipitation during self-healing were simulated. A permeability modeling of self-healing, combined with numerical simulation of calcium carbonate formation, was proposed based on the modified Poiseuille flow model. Moreover, the percentage of calcium carbonate in healing products was measured by TG-DTA. The simulated results show that self-healing can be dramatically promoted with the increase of pH and Ca2+ concentration. The calculated result of permeability is consistent with that measured for cracks appearing in middle or later stages of self-healing, it indicates that this model can be used to predict the self-healing rate to some extent. In addition, TG-DTA results show that the percentage of calcium carbonate in healing products is higher for mortar with only chemical expansion additives or cracks appearing in the later stage, which can more accurately predict the self-healing rate for the model.

Evolution and Development of the Information Concept in Biological Systems: From Empirical Description to Informational Modeling of the Living Structures

With the purpose to smooth the way of a correct understanding of information concepts and their evolution,in this paper,is discussed the evolution and development of the concept of information in biological systems,showing that this concept was intuitively perceived even since ancient times by our predecessors,and described according to their language level of that times,but the crystallization of the real meaning of information is an achievement of our nowadays,by successive contribution of various scientific branches and personalities of the scientific community of the world,leading to a modern description/modeling of reality,in which information plays a fundamental role.It is shown that our reality can be understood as a contribution of matter/energy/information and represented/discussed as the model of the Universal Triangle of Reality(UTR),where various previous models can be suggestively inserted,as a function of their basic concern.The modern concepts on information starting from a theoretic experiment which would infringe the thermodynamics laws and reaching the theory of information and modern philosophic concepts on the world structuration allow us to show that information is a fundamental component of the material world and of the biological structures,in correlation with the structuration/destructuration processes of matter,involving absorption/release of information.Based on these concepts,is discussed the functionality of the biologic structures and is presented the informational model of the human body and living structures,as a general model of info-organization on the entire biological scale,showing that a rudimentary proto-consciousness should be operative even at the low-scale biological systems,because they work on the same principles,like the most developed bio-systems.The operability of biologic structures as informational devices is also pointed out.

Anisotropic Constitutive Modeling of Compressible Biological Tissue

The anisotropic continuum stored energy density (ACSED) functional is applied for accurate constitutive modeling of biological tissues and finite element implementation without the isochoric—volumetric split, the anisotropic—isotropic split, or the anisotropic invariant split. Related stress and elasticity tensors in the reference and current configurations are worked out. A new kinematic model is derived based on the tangent Poisson’s ratio as a cubic polynomial function of stretch. The ACSED model, along with the kinematic model, accurately fits uniaxial extension test data for compressible human skin, bovine articular cartilage, and human aorta samples.

Exact Solutions of Fractional-Order Biological Population Model

In this paper, the Adomian＇s decomposition method （ADM） is presented for finding the exact solutions of a more general biological population models. A new solution is constructed in power series. The fractional derivatives are described in the Caputo sense. To illustrate the reliability of the method, some examples are provided.

Development and Experimental Evaluation of a Steady-state Model for the Step-feed Biological Nitrogen Removal Process

In this article,a steady-state mathematical model was developed and experimentally evaluated to inves- tigate the effect of influent flow distribution and volume ratios of anoxic and aerobic zones in each stage on the to- tal nitrogen concentration of the effluent in the step-feed biological nitrogen removal process.Unlike the previous modeling methods,this model can be used to calculate the removal rates of ammonia and nitrate in each stage and thereby predict the concentrations of ammonia,nitrate,and total nitrogen in the effluent.To verify the simulation results,pilot-scale experimental studies were carried out in a four-stage step feed process.Good correlations were achieved between the measured data and the simulation results,which proved the validity of the developed model. The sensitivity of the model predictions was analyzed.After verification of the validity,the step feed process was optimally operated for five months using the model and the criteria developed for the design and operation.During the pilot-scale experimental period,the effluent total nitrogen concentrations were all below 5mg·L -1 ,with more than 90%removal efficiency.

Establishment of injury models in studies of biological effects induced by microwave radiation

Microwave radiation has been widely used in various fields,such as communication,industry,medical treatment,and military applications.Microwave radiation may cause injuries to both the structures and functions of various organs,such as the brain,heart,reproductive organs,and endocrine organs,which endanger human health.Therefore,it is both theoretically and clinically important to conduct studies on the biological effects induced by microwave radiation.The successful establishment of injury models is of great importance to the reliability and reproducibility of these studies.In this article,we review the microwave exposure conditions,subjects used to establish injury models,the methods used for the assessment of the injuries,and the indicators implemented to evaluate the success of injury model establishment in studies on biological effects induced by microwave radiation.

3D Modelling of Biological Systems for Biomimetics

With the advanced development of computer-based enabling technologies, many engineering, medical, biology, chemistry, physics and food science etc have developed to the unprecedented levels, which lead to many research and development interests in various multi-discipline areas. Among them, biomimetics is one of the most promising and attractive branches of study. Biomimetics is a branch of study that uses biological systems as a model to develop synthetic systems. To learn from nature, one of the fundamental issues is to understand the natural systems such animals, insects, plants and human beings etc. The geometrical characterization and representation of natural systems is an important fundamental work for biomimetics research. 3D modeling plays a key role in the geometrical characterization and representation, especially in computer graphical visualization. This paper firstly presents the typical procedure of 3D modelling methods and then reviews the previous work of 3D geometrical modelling techniques and systems developed for industrial, medical and animation applications. Especially the paper discusses the problems associated with the existing techniques and systems when they are applied to 3D modelling of biological systems. Based upon the discussions, the paper proposes some areas of research interests in 3D modelling of biological systems and for Biomimetics.

Plasma-activated hydrogel:fabrication,functionalization,and effective biological model

Hydrogels are biomaterials with 3D networks of hydrophilic polymers.The generation of hydrogels is turning to the development of hydrogels with the help of enabling technologies.Plasma can tailor the hydrogels’properties through simultaneous physical and chemical actions,resulting in an emerging technology of plasma-activated hydrogels(PAH).PAH can be divided into functional PAH and biological tissue model PAH.This review systematically introduces the plasma sources,plasma etching polymer surface,and plasma cross-linking involved in the fabrication of PAH.The‘diffusion-drift-reaction model’is used to study the microscopic physicochemical interaction between plasma and biological tissue PAH models.Finally,the main achievements of PAH,including wound treatment,sterilization,3D tumor model,etc,and their development trends are discussed.

Homotopy Analysis Method for Solving Biological Population Model

In this paper,the homotopy analysis method (HAM) is applied to solve generalized biological populationmodels.The fractional derivatives are described by Caputo's sense.The method introduces a significant improvementin this field over existing techniques.Results obtained using the scheme presented here agree well with the analyticalsolutions and the numerical results presented in Ref.[6].However,the fundamental solutions of these equations stillexhibit useful scaling properties that make them attractive for applications.

Positive Almost Periodic Solution on a Nonlinear Logistic Biological Model with Grazing Rates

In this paper, we study the following nonlinear biological modeldx(t)/dt = x(t)[a(t)-b(t)x α (t)] + f(t, xt),by using fixed pointed theorem, the sufficient conditions of the existence of unique positive almost periodic solution for the above system are obtained, by using the theories of stability, the sufficient conditions which guarantee the stability of the positive almost periodic solution are derived.

Establishment and Analysis of Regression Models between Sowing Time and Plant Productivity, Biological Yield of Forage Sorghum in Autumn Idle Land

[Objective]The aim was to establish the linear regression prediction models between sowing time and plant productivity, biological yield of forage sorghum in autumn idle land.[Method]The relationships between sowing time and plant productivity, biological yield of forage sorghum were simulated and compared by using field experiment and linear regression analysis.[Result] The sowing time had an important influence on the plant productivity and biological yield of forage sorghum in autumn idle land. The plant productivity and biological yield of forage sorghum both decreased with the delay of sowing time.The regression model between plant fresh weight and sowing time was ？fresh=0.618-0.015x; the regression model between plant dry weight and sowing time was ？dry=0.184-0.005x; and the regression model between biological yield and sowing time was yield=29 126.461-711.448x. During July 23rd to August 30th, when the sowing time was delayed by 1 day, the plant fresh weight of forage sorghum was reduced by 0.015 g, the plant dry weight was reduced by 0.005 g, and the yield was reduced by 711.448 kg/hm2. [Conclusion] The three regression models established in this study will provide theoretical support for the production of forage sorghum.

Analysis of Modeling the Influence of Electromagnetic Fields Radiated by Industrial Static Converters and Impacts on Operators Using Maxwell’s Equations

The study of Electromagnetic Compatibility is essential to ensure the harmonious operation of electronic equipment in a shared environment. The basic principles of Electromagnetic Compatibility focus on the ability of devices to withstand electromagnetic disturbances and not produce disturbances that could affect other systems. Imperceptible in most work situations, electromagnetic fields can, beyond certain thresholds, have effects on human health. The objective of the present article is focused on the modeling analysis of the influence of geometric parameters of industrial static converters radiated electromagnetic fields using Maxwell’s equations. To do this we used the analytical formalism for calculating the electromagnetic field emitted by a filiform conductor, to model the electromagnetic radiation of this device in the spatio-temporal domain. The interactions of electromagnetic waves with human bodies are complex and depend on several factors linked to the characteristics of the incident wave. To model these interactions, we implemented the physical laws of electromagnetic wave propagation based on Maxwell’s and bio-heat equations to obtain consistent results. These obtained models allowed us to evaluate the spatial profile of induced current and temperature of biological tissue during exposure to electromagnetic waves generated by this system. The simulation 2D results obtained from computer tools show that the temperature variation and current induced by the electromagnetic field can have a very significant influence on the life of biological tissue. The paper provides a comprehensive analysis using advanced mathematical models to evaluate the influence of electromagnetic fields. The findings have direct implications for workplace safety, potentially influencing standards and regulations concerning electromagnetic exposure in industrial settings.

A three-dimensional coupled physical-biological model study in the spring of 1993 in the Bohai Sea of China

A three-dimensional （3-D） coupled physical and biological model was used to investigate the physical processes and their influence on the ecosystem dynamics of the Bohai Sea of China. The physical processes include M2 tide, time - varying wind forcing and river discharge. Wind records from 1 to 31 May in 1993 were selected to force the model. The biological model is based on a simple, nitrate and phosphate limited, lower trophic food web system. The simulated results showed that variation of residual currents forced by M2 tide, fiver discharge and time-varying wind had great impact on the distribution of phytoplankton biomass in the Laizhou Bay. High phytoplankton biomass appeared in the upwelling region. Numerical experiments based on the barotropic model and baroclinic model with no wind and water discharge were also conducted. Differences in the results by the baroclinic model and the barotropic model were significant： more patches appeared in the baroclinic model comparing with the barotropic model. And in the baroclinic model, the subsurface maximum phytoplankton biomass patches formed in the stratified water.

Study on optimization of parameters in a biological model

According to the data observed in a China- Japan Joint Investigation, the parameters of an ecosystem dynamics model (Qiao et al., 2000) were optimized. The values of eighteen parameters for the model were obtained, with nutrient half saturation constant, Kn= 1.4μmol/dm3, Kp = 0.129 μmol/dm3 and K3= 1. 16μmol/dm3 for the diatom and Kn= 0.345μmol/dm3, Kp=0. 113μmol/dm3 for the flagellate. The proposals to set up a function for this multiple objective problem were discussed in detail.

Stochastic Computational Heuristic for the Fractional Biological Model Based on Leptospirosis

The purpose of these investigations is to find the numerical outcomes of the fractional kind of biological system based on Leptospirosis by exploiting the strength of artificial neural networks aided by scale conjugate gradient,called ANNs-SCG.The fractional derivatives have been applied to get more reliable performances of the system.The mathematical form of the biological Leptospirosis system is divided into five categories,and the numerical performances of each model class will be provided by using the ANNs-SCG.The exactness of the ANNs-SCG is performed using the comparison of the reference and obtained results.The reference solutions have been obtained by using theAdams numerical scheme.For these investigations,the data selection is performed at 82%for training,while the statics for both testing and authentication is selected as 9%.The procedures based on the recurrence,mean square error,error histograms,regression,state transitions,and correlation will be accomplished to validate the fitness,accuracy,and reliability of the ANNs-SCG scheme.

A T-Cell Model for the Biological Role of Selenium-Dependent Glutathione Peroxidase

The cytosolic form of selenium-dependent glutathione peroxidase detoxifies both hydrogen and lipid peroxides and therefore represents a major component of the cellular anti-oxidant defenses. In order to study the biological role of this enzyme, we generated an expression construct in a retroviral vector, which when introduced into immortalized human T-cells, resulted in significant increases in the activity of this important enzyme. This effect is stable over extended maintenance in culture. The anti-oxidant defenses in these same cells are also shown to be attenuated hy chemically reducing cellular glutathione levels. Collectively, the abllity to both increase and decrease the anti-oxidant defenses in human T cells results in a useful model system for the study of oxidative stress and signaling in this cell type

A weakly coupled data assimilation system of a coupled physical–biological model for the northeastern South China Sea

A weakly coupled data assimilation system was established for a coupled physical–biological model for the northeastern South China Sea（NSCS）. The physical model used was the Regional Ocean Modeling System; the biological component was a seven-compartment nitrogen–phytoplankton–zooplankton–detritus ecosystem model; and the data assimilation method was Ensemble Optical Interpolation. To test the performance of the weakly coupled data assimilation system, two numerical experiments（i.e. control and assimilation runs） based on a process-oriented idealized case were conducted, and climatological SST was assimilated in the assimilation run. Only physical variables were adjusted in the weakly coupled data assimilation. The results showed that both the assimilated SST and other unassimilated physical variables had reasonable process responses. Due to the warmer SST observation, the water temperature（salinity） in the assimilation run increased（decreased） in coastal upwelling regions. Both the alongshore and bottom cross-shore currents were reduced, jointly demonstrating the weakening of the upwelling system. Meanwhile, ecosystem variables were also affected to some extent by the SST assimilation through the coupled model. For example, larger phytoplankton（chlorophyll） productivity was found in the upwelling region within the shallow layer due to the warmer waters in the assimilation run. Hence, the application of this data assimilation system could reasonably modify both physical and biological variables for the NSCS by SST assimilation.