Achievements of Truss Models for Reinforced Concrete Structures

Achievements are presented for truss models of RC structures developed in previous years: 1. Two constitutive models, biaxial and triaxial, are based on regular trusses, with bars obeying nonlinear uniaxial σ-ε laws of material under simulation;both models have been compared with test results and show a dependence of Poisson ratio on curvature of σ-ε law. 2. A truss finite element has been used in the nonlinear static and dynamic analysis of plane RC frames;it has been compared with test results and describes, in a simple way, the formation of plastic hinges. 3. Thanks to the very simple geometry of a truss, the equilibrium equations can be easily written and the stiffness matrix can be easily updated, both with respect to the deformed truss, within each step of a static incremental loading or within each time step of a dynamic analysis, so that to take into account geometric nonlinearities. So the confinement of a RC column is interpreted as a structural stability effect of concrete. And a significant role of the transverse reinforcement is revealed, that of preventing, by its close spacing and sufficient amount, the buckling of inner longitudinal concrete struts, which would lead to a global instability of the RC column. 4. The proposed truss model is statically indeterminate, so it exhibits some features, which are not met by the “strut-and-tie” model.

Differences in pathological changes between two rat models of severe traumatic brain injury

The rat high-impact free weight drop model mimics the diffuse axonal injury caused by severe traumatic brain injury in humans,while severe controlled cortical impact can produce a severe traumatic brain injury model using precise strike parameters.In this study,we compare the pathological mechanisms and pathological changes between two rat severe brain injury models to identify the similarities and differences.The severe controlled cortical impact model was produced by an electronic controlled cortical impact device,while the severe free weight drop model was produced by dropping a 500 g free weight from a height of 1.8 m through a plastic tube.Body temperature and mortality were recorded,and neurological deficits were assessed with the modified neurological severity score.Brain edema and bloodbrain barrier damage were evaluated by assessing brain water content and Evans blue extravasation.In addition,a cytokine array kit was used to detect inflammatory cytokines.Neuronal apoptosis in the brain and brainstem was quantified by immunofluorescence staining.Both the severe controlled cortical impact and severe free weight drop models exhibited significant neurological impairments and body temperature fluctuations.More severe motor dysfunction was observed in the severe controlled cortical impact model,while more severe cognitive dysfunction was observed in the severe free weight drop model.Brain edema,inflammatory cytokine changes and cortical neuronal apoptosis were more substantial and blood-brain barrier damage was more focal in the severe controlled cortical impact group compared with the severe free weight drop group.The severe free weight drop model presented with more significant apoptosis in the brainstem and diffused blood-brain barrier damage,with higher mortality and lower repeatability compared with the severe controlled cortical impact group.Severe brainstem damage was not found in the severe controlled cortical impact model.These results indicate that the severe controlled cortical impact model is relatively more stable,more reproducible,and shows obvious cerebral pathological changes at an earlier stage.Therefore,the severe controlled cortical impact model is likely more suitable for studies on severe focal traumatic brain injury,while the severe free weight drop model may be more apt for studies on diffuse axonal injury.All experimental procedures were approved by the Ethics Committee of Animal Experiments of Tianjin Medical University,China(approval No.IRB2012-028-02)in Febru ary 2012.

Exploiting fly models to investigate rare human neurological disorders

Rare neurological diseases,while individually are rare,collectively impact millions globally,leading to diverse and often severe neurological symptoms.Often attributed to genetic mutations that disrupt protein function or structure,understanding their genetic basis is crucial for accurate diagnosis and targeted therapies.To investigate the underlying pathogenesis of these conditions,researchers often use non-mammalian model organisms,such as Drosophila(fruit flies),which is valued for their genetic manipulability,cost-efficiency,and preservation of genes and biological functions across evolutionary time.Genetic tools available in Drosophila,including CRISPR-Cas9,offer a means to manipulate gene expression,allowing for a deep exploration of the genetic underpinnings of rare neurological diseases.Drosophila boasts a versatile genetic toolkit,rapid generation turnover,and ease of large-scale experimentation,making it an invaluable resource for identifying potential drug candidates.Researchers can expose flies carrying disease-associated mutations to various compounds,rapidly pinpointing promising therapeutic agents for further investigation in mammalian models and,ultimately,clinical trials.In this comprehensive review,we explore rare neurological diseases where fly research has significantly contributed to our understanding of their genetic basis,pathophysiology,and potential therapeutic implications.We discuss rare diseases associated with both neuron-expressed and glial-expressed genes.Specific cases include mutations in CDK19 resulting in epilepsy and developmental delay,mutations in TIAM1 leading to a neurodevelopmental disorder with seizures and language delay,and mutations in IRF2BPL causing seizures,a neurodevelopmental disorder with regression,loss of speech,and abnormal movements.And we explore mutations in EMC1 related to cerebellar atrophy,visual impairment,psychomotor retardation,and gain-of-function mutations in ACOX1 causing Mitchell syndrome.Loss-of-function mutations in ACOX1 result in ACOX1 deficiency,characterized by very-long-chain fatty acid accumulation and glial degeneration.Notably,this review highlights how modeling these diseases in Drosophila has provided valuable insights into their pathophysiology,offering a platform for the rapid identification of potential therapeutic interventions.Rare neurological diseases involve a wide range of expression systems,and sometimes common phenotypes can be found among different genes that cause abnormalities in neurons or glia.Furthermore,mutations within the same gene may result in varying functional outcomes,such as complete loss of function,partial loss of function,or gain-of-function mutations.The phenotypes observed in patients can differ significantly,underscoring the complexity of these conditions.In conclusion,Drosophila represents an indispensable and cost-effective tool for investigating rare neurological diseases.By facilitating the modeling of these conditions,Drosophila contributes to a deeper understanding of their genetic basis,pathophysiology,and potential therapies.This approach accelerates the discovery of promising drug candidates,ultimately benefiting patients affected by these complex and understudied diseases.

The pig as a preclinical traumatic brain injury model:current models,functional outcome measures,and translational detection strategies

Traumatic brain injury(TBI) is a major contributor of long-term disability and a leading cause of death worldwide. A series of secondary injury cascades can contribute to cell death, tissue loss, and ultimately to the development of functional impairments. However, there are currently no effective therapeutic interventions that improve brain outcomes following TBI. As a result, a number of experimental TBI models have been developed to recapitulate TBI injury mechanisms and to test the efficacy of potential therapeutics. The pig model has recently come to the forefront as the pig brain is closer in size, structure, and composition to the human brain compared to traditional rodent models, making it an ideal large animal model to study TBI pathophysiology and functional outcomes. This review will focus on the shared characteristics between humans and pigs that make them ideal for modeling TBI and will review the three most common pig TBI models–the diffuse axonal injury, the controlled cortical impact, and the fluid percussion models. It will also review current advances in functional outcome assessment measures and other non-invasive, translational TBI detection and measurement tools like biomarker analysis and magnetic resonance imaging. The use of pigs as TBI models and the continued development and improvement of translational assessment modalities have made significant contributions to unraveling the complex cascade of TBI sequela and provide an important means to study potential clinically relevant therapeutic interventions.

On Damped Wave Diffusion of Oxygen in Pancreatic Islets: Parabolic and Hyperbolic Models

Damped wave diffusion effects during oxygen transport in islets of Langerhans is studied. Simultaneous reaction and diffusion models were developed. The asymptotic limits of first and zeroth order in Michaelis and Menten kinetics was used in the study. Parabolic Fick diffusion and hyperbolic damped wave diffusion were studied separately. Method of relativistic transformation was used in order to obtain the solution for the hyperbolic model. Model solutions was used to obtain mass inertial times. Convective boundary condition was used. Sharma number (mass) may be used in evaluating the importance of the damped wave diffusion process in relation to other processes such as convection, Fick steady diffusion in the given application. Four regimes can be identified in the solution of hyperbolic damped wave diffusion model. These are;1) Zero Transfer Inertial Regime, 0 0≤τ≤τinertia;2) Rising Regime during times greater than inertial regime and less than at the wave front, Xp > τ, 3) at Wave front , τ = Xp;4) Falling Regime in open Interval, of times greater than at the wave front, τ > Xp. Method of superposition of steady state concentration and transient concentration used in both solutions of parabolic and hyperbolic models. Expression for steady state concentration developed. Closed form analytic model solutions developed in asymptotic limits of Michaelis and Menten kinetic at zeroth order and first order. Expression for Penetration Length Derived-Hypoxia Explained. Expression for Inertial Lag Time Derived. Solution was obtained by the method of separation of variables for transient for parabolic model and by the method of relativistic transformation for hyperbolic models. The concentration profile was expressed as a sum of steadty state and transient parts.

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.

Mathematical Wave Functions and 3D Finite Element Modelling of the Electron and Positron

The wave/particle duality of particles in Physics is well known. Particles have properties that uniquely characterize them from one another, such as mass, charge and spin. Charged particles have associated Electric and Magnetic fields. Also, every moving particle has a De Broglie wavelength determined by its mass and velocity. This paper shows that all of these properties of a particle can be derived from a single wave function equation for that particle. Wave functions for the Electron and the Positron are presented and principles are provided that can be used to calculate the wave functions of all the fundamental particles in Physics. Fundamental particles such as electrons and positrons are considered to be point particles in the Standard Model of Physics and are not considered to have a structure. This paper demonstrates that they do indeed have structure and that this structure extends into the space around the particle’s center (in fact, they have infinite extent), but with rapidly diminishing energy density with the distance from that center. The particles are formed from Electromagnetic standing waves, which are stable solutions to the Schrödinger and Classical wave equations. This stable structure therefore accounts for both the wave and particle nature of these particles. In fact, all of their properties such as mass, spin and electric charge, can be accounted for from this structure. These particle properties appear to originate from a single point at the center of the wave function structure, in the same sort of way that the Shell theorem of gravity causes the gravity of a body to appear to all originate from a central point. This paper represents the first two fully characterized fundamental particles, with a complete description of their structure and properties, built up from the underlying Electromagnetic waves that comprise these and all fundamental particles.

Genetic Worth Effect Models for Boreal Conifers and Their Utility When Integrated into Density Management Decision-Support Systems

Based on approaches deduced from previous research findings and empirical observations from density control experiments, genetic worth effect response models were developed for black spruce (Picea mariana (Mill) BSP.) and jack pine (Pinus banksiana Lamb.) plantations. The models accounted for the increased rate of stand development arising from the planting of genetically-improved stock through temporal adjustments to the species-specific site-based mean dominant height-age functions. The models utilized a relative height growth modifier based on known estimates of genetic gain. The models also incorporated a phenotypic juvenile age-mature age correlation function in order to account for the intrinsic temporal decline in the magnitude of genetic worth effects throughout the rotation. Integrating the functions into algorithmic variants of structural stand density management models produced stand development patterns that were consistent with axioms of even-aged stand dynamics.

A Study of Bilinear Models in Voice Conversion

This paper presents a voice conversion technique based on bilinear models and introduces the concept of contextual modeling. The bilinear approach reformulates the spectral envelope representation from line spectral frequencies feature to a two-factor parameterization corresponding to speaker identity and phonetic information, the so-called style and content factors. This decomposition offers a flexible representation suitable for voice conversion and facilitates the use of efficient training algorithms based on singular value decomposition. In a contextual approach (bilinear) models are trained on subsets of the training data selected on the fly at conversion time depending on the characteristics of the feature vector to be converted. The performance of bilinear models and context modeling is evaluated in objective and perceptual tests by comparison with the popular GMM-based voice conversion method for several sizes and different types of training data.

Can mouse models mimic sporadic Alzheimer’s disease?

Alzheimer’s disease(AD)is a progressive neurodegenerative disorder and the most common form of dementia worldwide.As age is the main risk factor,>97%of all AD cases are of sporadic origin,potentiated by various risk factors associated with life style and starting at an age>60 years.Only<3%of AD cases are of genetic origin caused by mutations in the amyloid precursor protein or Presenilins 1 or 2,and symptoms already start at an age<30 years.In order to study progression of AD,as well as therapeutic strategies,mouse models are state-of-the-art.So far many transgenic mouse models have been developed and used,with mutations in the APP or presenilin or combinations(3×Tg,5×Tg).However,such transgenic mouse models more likely mimic the genetic form of AD and no information can be given how sporadic forms develop.Several risk genes,such as Apolipoprotein E4 and TREM-2 enhance the risk of sporadic AD,but also many risk factors associated with life style(e.g.,diabetes,hypercholesterolemia,stress)may play a role.In this review we discuss the current situation regarding AD mouse models,and the problems to develop a sporadic mouse model of AD.

How Accurately Contemporary Models Can Predict Monsoons?

Seasonal changes exhibit climate changes, so models can predict future climate change accurately only if they can reproduce seasonal cycle accu-rately. Further, seasonal changes are much larger than the changes even in long period of centuries. Thus it is unwise to ignore large ones compared to small climate change. In this paper, we determine how accurately a suite of ten coupled general circulation models reproduce the observed seasonal cycle in rainfall of the tropics. The seasonal cycles in rainfall of global tropics are known as monsoons. We found that the models can reasonably reproduce the seasonal cycle in rainfall, thus are useful in climate prediction and simulation of global monsoons.

Statistical Inference in Generalized Linear Mixed Models by Joint Modelling Mean and Covariance of Non-Normal Random Effects

Generalized linear mixed models (GLMMs) are typically constructed by incorporating random effects into the linear predictor. The random effects are usually assumed to be normally distributed with mean zero and variance-covariance identity matrix. In this paper, we propose to release random effects to non-normal distributions and discuss how to model the mean and covariance structures in GLMMs simultaneously. Parameter estimation is solved by using Quasi-Monte Carlo (QMC) method through iterative Newton-Raphson (NR) algorithm very well in terms of accuracy and stabilization, which is demonstrated by real binary salamander mating data analysis and simulation studies.

Optimal Placement of Multi DG Units Including Different Load Models Using PSO

This paper proposes a multi-objective index-based approach to optimally determine the size and location of multi-distributed generators (DG) units in distribution system with different load models. It is shown that load models can significantly affect the optimal location and sizing of DG resources in distribution systems. The proposed multi-objective function to be optimized includes a short circuit level parameter to represent the protective device requirements. The proposed function also considers a wide range of technical issues such as active and reactive power losses of the system, the voltage profile, the line loading and the MVA intake by the grid. The optimization technique based on particle swarm optimization (PSO) is introduced. The analysis of continuation power flow to determine the effect of DG units on the most sensitive buses to voltage collapse is carried out. The proposed algorithm is tested using the 38-bus radial system and the IEEE 30-bus meshed system. The results show the effectiveness of the proposed algorithm.

On the Cosmic Evolution of the Quantum Vacuum Using Two Variable G Models and Winterberg’s Thesis

We work within a Winterberg framework where space, i.e., the vacuum, consists of a two component superfluid/super-solid made up of a vast assembly (sea) of positive and negative mass Planck particles, called planckions. These material particles interact indirectly, and have very strong restoring forces keeping them a finite distance apart from each other within their respective species. Because of their mass compensating effect, the vacuum appears massless, charge-less, without pressure, net energy density or entropy. In addition, we consider two varying G models, where G, is Newton’s constant, and G-1, increases with an increase in cosmological time. We argue that there are at least two competing models for the quantum vacuum within such a framework. The first follows a strict extension of Winterberg’s model. This leads to nonsensible results, if G increases, going back in cosmological time, as the length scale inherent in such a model will not scale properly. The second model introduces a different length scale, which does scale properly, but keeps the mass of the Planck particle as, ± the Planck mass. Moreover we establish a connection between ordinary matter, dark matter, and dark energy, where all three mass densities within the Friedman equation must be interpreted as residual vacuum energies, which only surface, once aggregate matter has formed, at relatively low CMB temperatures. The symmetry of the vacuum will be shown to be broken, because of the different scaling laws, beginning with the formation of elementary particles. Much like waves on an ocean where positive and negative planckion mass densities effectively cancel each other out and form a zero vacuum energy density/zero vacuum pressure surface, these positive mass densities are very small perturbations (anomalies) about the mean. This greatly alleviates, i.e., minimizes the cosmological constant problem, a long standing problem associated with the vacuum.

Neurophysiological, histological, and behavioral characterization of animal models of distraction spinal cord injury: a systematic review

Distraction spinal cord injury is caused by some degree of distraction or longitudinal tension on the spinal cord and commonly occurs in patients who undergo corrective operation for severe spinal deformity.With the increased degree and duration of distraction,spinal cord injuries become more serious in terms of their neurophysiology,histology,and behavior.Very few studies have been published on the specific characteristics of distraction spinal cord injury.In this study,we systematically review 22 related studies involving animal models of distraction spinal cord injury,focusing particularly on the neurophysiological,histological,and behavioral characteristics of this disease.In addition,we summarize the mechanisms underlying primary and secondary injuries caused by distraction spinal cord injury and clarify the effects of different degrees and durations of distraction on the primary injuries associated with spinal cord injury.We provide new concepts for the establishment of a model of distraction spinal cord injury and related basic research,and provide reference guidelines for the clinical diagnosis and treatment of this disease.

Torsional Models of Two-ply Yarn

In this paper,the vector equation of a generaliseddoubly wound helix was derived.Treloar’s pliedyarn geometry could be obtained as a special case ofthe generalised doubly wound helix.The shortest fi-bre length around the surface of a helical tube(formed by fibre helices)was determined by apply-ing variational principles.The fibre length as calcu-lated by using Treloar’s geometry was compared in-directly with the shortest possible fibre length at dif-ferent levels of yarn deformation when some of Tre-loar’s rigid geometrical constraints were relaxed.Anew idea based on non-concentric circles was intro-duced to approximate the fibre helix movement in atwo-ply yarn.A torsional model of two-ply yarnwas developed and the theoretical predictions werecompared with some preliminary experimental re-sults.

Basic Experimental Pancreatitis Models for Beginners

Efforts to find an ideal model for pancreatitis date back to 1960’s. Many models are suggested since then. Every model has its own advantages and disadvantages. Some of these models test etiology while others simulate the complications of pancreatitis. An ideal model which by itself demonstrates all aspects of pancreatitis including systemic changes is yet to be described. In this review we tried to gather the basic, easy to construct models.

Nonlinear mixed-effects height to crown base and crown length dynamic models using the branch mortality technique for a Korean larch( Larix olgensis ) plantations in northeast China

Korean larch(Larix olgensis)is one of the main tree species for aff orestation and timber production in northeast China.However,its timber quality and growth ability are largely infl uenced by crown size,structure and shape.The majority of crown models are static models based on tree size and stand characteristics from temporary sample plots,but crown dynamic models has seldom been constructed.Therefore,this study aimed to develop height to crown base(HCB)and crown length(CL)dynamic models using the branch mortality technique for a Korean larch plantation.The nonlinear mixed-eff ects model with random eff ects,variance functions and correlation structures,was used to build HCB and CL dynamic models.The data were obtained from 95 sample trees of 19 plots in Meng JiaGang forest farm in Northeast China.The results showed that HCB progressively increases as tree age,tree height growth(HT growth)and diameter at breast height growth(DBH growth).The CL was increased with tree age in 20 years ago,and subsequently stabilized.HT growth,DBH growth stand basal area(BAS)and crown competition factor(CCF)signifi cantly infl uenced HCB and CL.The HCB was positively correlated with BAS,HT growth and DBH growth,but negatively correlated with CCF.The CL was positively correlated with BAS and CCF,but negatively correlated with DBH growth.Model fi tting and validation confi rmed that the mixed-eff ects model considering the stand and tree level random eff ects was accurate and reliable for predicting the HCB and CL dynamics.However,the models involving adding variance functions and time series correlation structure could not completely remove heterogeneity and autocorrelation,and the fi tting precision of the models was reduced.Therefore,from the point of view of application,we should take care to avoid setting up over-complex models.The HCB and CL dynamic models in our study may also be incorporated into stand growth and yield model systems in China.

Effects of rotation and gravity on an electro-magneto-thermoelastic medium with diffusion and voids by using the Lord-Shulman and dual-phase-lag models

The effects of rotation and gravity on an electro-magneto-thermoelastic medium with diffusion and voids in a generalized thermoplastic half-space are studied by using the Lord-Shulman (L-S) model and the dual-phase-lag (DPL) model. The analytical solutions for the displacements, stresses, temperature, diffusion concentration, and volume fraction field with different values of the magnetic field, the rotation, the gravity, and the initial stress are obtained and portrayed graphically. The results indicate that the effects of gravity, rotation, voids, diffusion, initial stress, and electromagnetic field are very pronounced on the physical properties of the material.

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.