Theoretical investigation on axial cyclic performance of monopile in sands using interface constitutive models

Cyclic loads generated by environmental factors,such as winds,waves,and trains,will likely lead to performance degradation in pile foundations,resulting in issues like permanent displacement accumulation and bearing capacity attenuation.This paper presents a semi-analytical solution for predicting the axial cyclic behavior of piles in sands.The solution relies on two enhanced nonlinear load-transfer models considering stress-strain hysteresis and cyclic degradation in the pile-soil interaction.Model parameters are calibrated through cyclic shear tests of the sand-steel interface and laboratory geotechnical testing of sands.A novel aspect involves the meticulous formulation of the shaft loadtransfer function using an interface constitutive model,which inherently inherits the interface model’s advantages,such as capturing hysteresis,hardening,degradation,and particle breakage.The semi-analytical solution is computed numerically using the matrix displacement method,and the calculated values are validated through model tests performed on non-displacement and displacement piles in sands.The results demonstrate that the predicted values show excellent agreement with the measured values for both the static and cyclic responses of piles in sands.The displacement pile response,including factors such as bearing capacity,mobilized shaft resistance,and convergence rate of permanent settlement,exhibit improvements compared to non-displacement piles attributed to the soil squeezing effect.This methodology presents an innovative analytical framework,allowing for integrating cyclic interface models into the theoretical investigation of pile responses.

Theoretical models for designing a 220-GHz folded waveguide backward wave oscillator

In this paper, the basic equations of beam-wave interaction for designing the 220 GHz folded waveguide （FW） backward wave oscillator （BWO） are described. On the whole, these equations are mainly classified into small signal model （SSM）, large signal model （LSM）, and simplified small signal model （SSSM）. Using these linear and nonlinear one-dimensional （1D） models, the oscillation characteristics of the FW BWO of a given configuration of slow wave struc- ture （SWS） can be calculated by numerical iteration algorithm, which is more time efficient than three-dimensional （3D） particle-in-cell （PIC） simulation. The SSSM expressed by analytical formulas is innovatively derived for determining the initial values of the FW SWS conveniently. The dispersion characteristics of the FW are obtained by equivalent circuit analysis. The space charge effect, the end reflection effect, the lossy wall effect, and the relativistic effect are all considered in our models to offer more accurate results. The design process of the FW BWO tube with output power of watt scale in a frequency range between 215 GHz and 225 GHz based on these 1D models is demonstrated. The 3D PIC method is adopted to verify the theoretical design results, which shows that they are in good agreement with each other.

The Application of Theoretical Models in the Studies of Physical Activity Behaviors of the Elderly in China

By using the method of literature review, this paper introduces the popular theoretical models which have shown to better explain physical activity behaviors at a certain degree, summarizes the dominating theoretical models in the studies of physical activity behaviors of the elderly in China. In addition, shortcomings and future prospects are pointed out at the end.

Dynamics of Advantageous Mutant Spread in Spatial Death-Birth and Birth-Death Moran Models

The spread of an advantageous mutation through a population is of fundamental interest in population genetics. While the classical Moran model is formulated for a well-mixed population, it has long been recognized that in real-world applications, the population usually has an explicit spatial structure which can significantly influence the dynamics. In the context of cancer initiation in epithelial tissue, several recent works have analyzed the dynamics of advantageous mutant spread on integer lattices, using the biased voter model from particle systems theory. In this spatial version of the Moran model, individuals first reproduce according to their fitness and then replace a neighboring individual. From a biological standpoint, the opposite dynamics, where individuals first die and are then replaced by a neighboring individual according to its fitness, are equally relevant. Here, we investigate this death-birth analogue of the biased voter model. We construct the process mathematically, derive the associated dual process, establish bounds on the survival probability of a single mutant, and prove that the process has an asymptotic shape. We also briefly discuss alternative birth-death and death-birth dynamics, depending on how the mutant fitness advantage affects the dynamics. We show that birth-death and death-birth formulations of the biased voter model are equivalent when fitness affects the former event of each update of the model, whereas the birth-death model is fundamentally different from the death-birth model when fitness affects the latter event.

Xinhe Mine water inrush risk assessment based on quantification theoretical models

Taking the Xinhe mine's structure, mine pressure, structural fissure, fault andfault displacement, the distance between fault and water inrush point, thickness of block,water pressure those geological factors which influenced the water inrush as the independentvariable, based on these data of water inrush point and water uninrush point, usingthe method of quantification theory(Ⅰ,Ⅱ), it would quantitatively disposes the qualitativevariable, applied to calculation to evaluate the risk of Xinhe's water inrush.

Theoretical and Experimental Sets of Choice Anode/Cathode Architectonics for High-Performance Full-Scale LIB Built-up Models

To control the power hierarchy design of lithium-ion battery(LIB)builtup sets for electric vehicles(EVs),we offer intensive theoretical and experimental sets of choice anode/cathode architectonics that can be modulated in full-scale LIB built-up models.As primary structural tectonics,heterogeneous composite superstructures of full-cell-LIB(anode//cathode)electrodes were designed in closely packed flower agave rosettes TiO2@C(FRTO@C anode)and vertical-star-tower LiFePO4@C(VST@C cathode)building blocks to regulate the electron/ion movement in the three-dimensional axes and orientation pathways.The superpower hierarchy surfaces and multi-directional orientation components may create isosurface potential electrodes with mobile electron movements,in-to-out interplay electron dominances,and electron/charge cloud distributions.This study is the first to evaluate the hotkeys of choice anode/cathode architectonics to assemble different LIB-electrode platforms with high-mobility electron/ion flows and high-performance capacity functionalities.Density functional theory calculation revealed that the FRTO@C anode and VST-(i)@C cathode architectonics are a superior choice for the configuration of full-scale LIB built-up models.The integrated FRTO@C//VST-(i)@C full-scale LIB retains a huge discharge capacity(~94.2%),an average Coulombic efficiency of 99.85%after 2000 cycles at 1 C,and a high energy density of 127 Wh kg?1,thereby satisfying scale-up commercial EV requirements.

Theoretical Models of Space and Its Philosophical Category

Diverse concepts of space developed in history of natural philosophy,mathematics,physics,and other natural or cultural studies form theoretical models of spatial relations,given in human’s experience.Their diversity is due not only to the multiplicity of philosophical and methodological approaches to the concept of space,but also to the variety of ways,in which spatial relationships can be organized.This variety gives a possibility to distinct autonomous spaces of different types with diverse sets of properties as well as separate spaces with their own ordinal,metrical,and sequential structures.Particularly,various ways of space semiotization in culture generate different types of autonomous and separate spaces:written texts,maps,pictures,chessboards,etc.In the same time,all particular notions of space are included in a general logical class.Its volume and content are covered by the philosophical category of space.Such general category cannot be reduced to mathematical,physical,or other concepts of space elaborated in particular sciences,however,it serves as a philosophical basis for their comparison.

Evolution and Prospects of Foundation Models: From Large Language Models to Large Multimodal Models

Since the 1950s,when the Turing Test was introduced,there has been notable progress in machine language intelligence.Language modeling,crucial for AI development,has evolved from statistical to neural models over the last two decades.Recently,transformer-based Pre-trained Language Models(PLM)have excelled in Natural Language Processing(NLP)tasks by leveraging large-scale training corpora.Increasing the scale of these models enhances performance significantly,introducing abilities like context learning that smaller models lack.The advancement in Large Language Models,exemplified by the development of ChatGPT,has made significant impacts both academically and industrially,capturing widespread societal interest.This survey provides an overview of the development and prospects from Large Language Models(LLM)to Large Multimodal Models(LMM).It first discusses the contributions and technological advancements of LLMs in the field of natural language processing,especially in text generation and language understanding.Then,it turns to the discussion of LMMs,which integrates various data modalities such as text,images,and sound,demonstrating advanced capabilities in understanding and generating cross-modal content,paving new pathways for the adaptability and flexibility of AI systems.Finally,the survey highlights the prospects of LMMs in terms of technological development and application potential,while also pointing out challenges in data integration,cross-modal understanding accuracy,providing a comprehensive perspective on the latest developments in this field.

The relationship between compartment models and their stochastic counterparts:A comparative study with examples of the COVID-19 epidemic modeling

Deterministic compartment models(CMs)and stochastic models,including stochastic CMs and agent-based models,are widely utilized in epidemic modeling.However,the relationship between CMs and their corresponding stochastic models is not well understood.The present study aimed to address this gap by conducting a comparative study using the susceptible,exposed,infectious,and recovered(SEIR)model and its extended CMs from the coronavirus disease 2019 modeling literature.We demonstrated the equivalence of the numerical solution of CMs using the Euler scheme and their stochastic counterparts through theoretical analysis and simulations.Based on this equivalence,we proposed an efficient model calibration method that could replicate the exact solution of CMs in the corresponding stochastic models through parameter adjustment.The advancement in calibration techniques enhanced the accuracy of stochastic modeling in capturing the dynamics of epidemics.However,it should be noted that discrete-time stochastic models cannot perfectly reproduce the exact solution of continuous-time CMs.Additionally,we proposed a new stochastic compartment and agent mixed model as an alternative to agent-based models for large-scale population simulations with a limited number of agents.This model offered a balance between computational efficiency and accuracy.The results of this research contributed to the comparison and unification of deterministic CMs and stochastic models in epidemic modeling.Furthermore,the results had implications for the development of hybrid models that integrated the strengths of both frameworks.Overall,the present study has provided valuable epidemic modeling techniques and their practical applications for understanding and controlling the spread of infectious diseases.

Theoretical research and practical application of Mathematical economic models

Mathematical economic modeling is widely used to provide a reference for policy makers and guidance for the specific work of many departments, such as saving expenditures, reducing costs and improving profit. Particularly, it can predict and estimate the future, playing a great role in promoting the rapid development of science and technology as well as the management of market economy. In general, mathematics does not directly deal with the objective conditions on the management of market economy. In order to use mathematics to solve problems in the field of the management of market economic, it is necessary to carry out mathematical economic modeling.

Comparison of two theoretical models for electric leak location at landfill

To solve the disability of conventional model used in electrical leak location when measurement electrodes were buried under the liner, a new model of high voltage DC leak detection is developed. For single-liner landfill, the waste material layer, the geomembrane liner and the soil under the liner are simulated with infinite horizontal layers. The leak is regarded as two parts, one being negative current source at the entrance, and the other positive current source of the same size at the exit. Comparisons between the new theoretical model and conventional model show that conventional model is efficient in locating leaks in geomembane liner associating the dipole scanning above the liner but is ineffective when the measurement electrodes were buried under the liner. The new theoretical model data are in excellent agreement with experimental data not only above the liner but also under the liner.

A Theoretical Study on Nonadiabatic Trapping Models of the Reaction NH+H←→N+H_2

The properties of nonadiabatic trapping models of the reaction NH+H -N+H, are investigated in a collinear model as \veil as a non-collinear thermal reaction on the basis of theintrinsic reaction coordinate (IRC) intbrmation obtained by ah initio calculations at QCISD/631 IG** ie\el. Using the unitied statistical theory fornonadiabatic trapping models. the thermal rateconstants over the temperature range of 2000-3000K are computed which are in excellent agreementwith the experiment results.

Theoretical Models of Light Scattering Applied in Sizing Particles in Coal Water Slurry

Advantges and disadvantage of Mie scattering model and Fraunhofer diffraction model are discussed. The result shows that 1) the Fraunhofer diffraction model is simple in design and fast in operation, which is quite suitable for on-line control and 2) the intensity and energy distribution of diffracted light of both the Mie scattering model and the Fraunhofer theoretical model are compared and researched. Feasibility of using the Fraunhofer diffraction model to replace the Mie scattering model in measuring particles in coal water slurry is demonstrated.

Analysis of the inflection points of height-diameter models

The inflection point is an important feature of sigmoidal height-diameter(H-D)models.It is often cited as one of the properties favoring sigmoidal model forms.However,there are very few studies analyzing the inflection points of H-D models.The goals of this study were to theoretically and empirically examine the behaviors of inflection points of six common H-D models with a regional dataset.The six models were the Wykoff(WYK),Schumacher(SCH),Curtis(CUR),HossfeldⅣ(HOS),von Bertalanffy-Richards(VBR),and Gompertz(GPZ)models.The models were first fitted in their base forms with tree species as random effects and were then expanded to include functional traits and spatial distribution.The distributions of the estimated inflection points were similar between the two-parameter models WYK,SCH,and CUR,but were different between the threeparameter models HOS,VBR,and GPZ.GPZ produced some of the largest inflection points.HOS and VBR produced concave H-D curves without inflection points for 12.7%and 39.7%of the tree species.Evergreen species or decreasing shade tolerance resulted in larger inflection points.The trends in the estimated inflection points of HOS and VBR were entirely opposite across the landscape.Furthermore,HOS could produce concave H-D curves for portions of the landscape.Based on the studied behaviors,the choice between two-parameter models may not matter.We recommend comparing seve ral three-parameter model forms for consistency in estimated inflection points before deciding on one.Believing sigmoidal models to have inflection points does not necessarily mean that they will produce fitted curves with one.Our study highlights the need to integrate analysis of inflection points into modeling H-D relationships.

Influence of material models on theoretical forming limit diagram prediction for Ti-6Al-4V alloy under warm condition

Forming limit diagram (FLD) is an important performance index to describe the maximum limit of principal strains that can be sustained by sheet metals till to the onset of localized necking. It offers a convenient and useful tool to predict the forming limit in the sheet metal forming processes. In the present study, FLD has been determined experimentally for Ti?6Al?4V alloy at 400 °C by conducting a Nakazima test with specimens of different widths. Additionally, for theoretical FLD prediction, various anisotropic yield criteria (Barlat 1989, Barlat 1996, Hill 1993) and different hardening models viz., Hollomon power law (HPL), Johnson?Cook (JC), modified Zerilli–Armstrong (m-ZA), modified Arrhenius (m-Arr) models have been developed. Theoretical FLDs have been determined using Marciniak and Kuczynski (M?K) theory incorporating the developed yield criteria and constitutive models. It has been observed that the effect of yield model is more pronounced than the effect of constitutive model for theoretical FLDs prediction. However, the value of thickness imperfection factor (f0) is solely dependent on hardening model. Hill (1993) yield criterion is best suited for FLD prediction in the right hand side region. Moreover, Barlat (1989) yield criterion is best suited for FLD prediction in left hand side region. Therefore, the proposed hybrid FLD in combination with Barlat (1989) and Hill (1993) yield models with m-Arr hardening model is in the best agreement with experimental FLD.

Progress in experimental models to investigate the in vivo and in vitro antidiabetic activity of drugs

Diabetes mellitus is one of the world's most prevalent and complex metabolic disorders,and it is a rapidly growing global public health issue.It is characterized by hyperglycemia,a condition involving a high blood glucose level brought on by deficiencies in insulin secretion,decreased activity of insulin,or both.Prolonged effects of diabetes include cardiovascular problems,retinopathy,neuropathy,nephropathy,and vascular alterations in both macro-and micro-blood vessels.In vivo and in vitro models have always been important for investigating and characterizing disease pathogenesis,identifying targets,and reviewing novel treatment options and medications.Fully understanding these models is crucial for the researchers so this review summarizes the different experimental in vivo and in vitro model options used to study diabetes and its consequences.The most popular in vivo studies involves the small animal models,such as rodent models,chemically induced diabetogens like streptozotocin and alloxan,and the possibility of deleting or overexpressing a specific gene by knockout and transgenic technologies on these animals.Other models include virally induced models,diet/nutrition induced diabetic animals,surgically induced models or pancreatectomy models,and non-obese models.Large animals or non-rodent models like porcine(pig),canine(dog),nonhuman primate,and Zebrafish models are also outlined.The in vitro models discussed are murine and human beta-cell lines and pancreatic islets,human stem cells,and organoid cultures.The other enzymatic in vitro tests to assess diabetes include assay of amylase inhibition and inhibition ofα-glucosidase activity.

Smaller & Smarter: Score-Driven Network Chaining of Smaller Language Models

With the continuous evolution and expanding applications of Large Language Models (LLMs), there has been a noticeable surge in the size of the emerging models. It is not solely the growth in model size, primarily measured by the number of parameters, but also the subsequent escalation in computational demands, hardware and software prerequisites for training, all culminating in a substantial financial investment as well. In this paper, we present novel techniques like supervision, parallelization, and scoring functions to get better results out of chains of smaller language models, rather than relying solely on scaling up model size. Firstly, we propose an approach to quantify the performance of a Smaller Language Models (SLM) by introducing a corresponding supervisor model that incrementally corrects the encountered errors. Secondly, we propose an approach to utilize two smaller language models (in a network) performing the same task and retrieving the best relevant output from the two, ensuring peak performance for a specific task. Experimental evaluations establish the quantitative accuracy improvements on financial reasoning and arithmetic calculation tasks from utilizing techniques like supervisor models (in a network of model scenario), threshold scoring and parallel processing over a baseline study.

A theoretical extraction scheme of transport information based on exclusion models

In order to explore how to extract more transport information from current fluctuation, a theoretical extraction scheme is presented in a single barrier structure based on exclusion models, which include counter-flows model and tunnel model. The first four cumulants of these two exclusion models are computed in a single barrier structure, and their characteristics are obtained. A scheme with the help of the first three cumulants is devised to check a transport process to follow the counter-flows model, the tunnel model or neither of them. Time series generated by Monte Carlo techniques is adopted to validate the abstraction procedure, and the result is reasonable.

Effects of mesenchymal stem cell on dopaminergic neurons,motor and memory functions in animal models of Parkinson's disease:a systematic review and meta-analysis

Parkinson’s disease is chara cterized by the loss of dopaminergic neurons in the substantia nigra pars com pacta,and although restoring striatal dopamine levels may improve symptoms,no treatment can cure or reve rse the disease itself.Stem cell therapy has a regenerative effect and is being actively studied as a candidate for the treatment of Parkinson’s disease.Mesenchymal stem cells are considered a promising option due to fewer ethical concerns,a lower risk of immune rejection,and a lower risk of teratogenicity.We performed a meta-analysis to evaluate the therapeutic effects of mesenchymal stem cells and their derivatives on motor function,memory,and preservation of dopamine rgic neurons in a Parkinson’s disease animal model.We searched bibliographic databases(PubMed/MEDLINE,Embase,CENTRAL,Scopus,and Web of Science)to identify articles and included only pee r-reviewed in vivo interve ntional animal studies published in any language through J une 28,2023.The study utilized the random-effect model to estimate the 95%confidence intervals(CI)of the standard mean differences(SMD)between the treatment and control groups.We use the systematic review center for laboratory animal expe rimentation’s risk of bias tool and the collaborative approach to meta-analysis and review of animal studies checklist for study quality assessment.A total of 33studies with data from 840 Parkinson’s disease model animals were included in the meta-analysis.Treatment with mesenchymal stem cells significantly improved motor function as assessed by the amphetamine-induced rotational test.Among the stem cell types,the bone marrow MSCs with neurotrophic factor group showed la rgest effect size(SMD[95%CI]=-6.21[-9.50 to-2.93],P=0.0001,I^(2)=0.0%).The stem cell treatment group had significantly more tyrosine hydroxylase positive dopamine rgic neurons in the striatum([95%CI]=1.04[0.59 to 1.49],P=0.0001,I^(2)=65.1%)and substantia nigra(SMD[95%CI]=1.38[0.89 to 1.87],P=0.0001,I^(2)=75.3%),indicating a protective effect on dopaminergic neurons.Subgroup analysis of the amphetamine-induced rotation test showed a significant reduction only in the intracranial-striatum route(SMD[95%CI]=-2.59[-3.25 to-1.94],P=0.0001,I^(2)=74.4%).The memory test showed significant improvement only in the intravenous route(SMD[95%CI]=4.80[1.84 to 7.76],P=0.027,I^(2)=79.6%).Mesenchymal stem cells have been shown to positively impact motor function and memory function and protect dopaminergic neurons in preclinical models of Parkinson’s disease.Further research is required to determine the optimal stem cell types,modifications,transplanted cell numbe rs,and delivery methods for these protocols.

Theoretical Modeling and Surface Roughness Prediction of Microtextured Surfaces in Ultrasonic Vibration-Assisted Milling

Textured surfaces with certain micro/nano structures have been proven to possess some advanced functions,such as reducing friction,improving wear and increasing wettability.Accurate prediction of micro/nano surface textures is of great significance for the design,fabrication and application of functional textured surfaces.In this paper,based on the kinematic analysis of cutter teeth,the discretization of ultrasonic machining process,transformation method of coordinate systems and the cubic spline data interpolation,an integrated theoretical model was established to characterize the distribution and geometric features of micro textures on the surfaces machined by different types of ultrasonic vibration-assisted milling(UVAM).Based on the theoretical model,the effect of key process parameters(vibration directions,vibration dimensions,cutting parameters and vibration parameters)on tool trajectories and microtextured surface morphology in UVAM is investigated.Besides,the effect of phase difference on the elliptical shape in 2D/3D ultrasonic elliptical vibration-assisted milling(UEVAM)was analyzed.Compared to conventional numerical models,the method of the cubic spline data interpolation is applied to the simulation of microtextured surface morphology in UVAM,which is more suitable for characterizing the morphological features of microtextured surfaces than traditional methods due to the presence of numerous micro textures.The prediction of surface roughness indicates that the magnitude of ultrasonic amplitude in z-direction should be strictly limited in 1D rotary UVAM,2D and 3D UEVAM due to the unfavorable effect of axial ultrasonic vibration on the surface quality.This study can provide theoretical guidance for the design and fabrication of microtextured surfaces in UVAM.