What can computational modeling offer for studying the Ca^(2+) dysregulation in Alzheimer's disease:current research and future directions

Ca^2＋ dysregulation is an early event observed in Alzheimer＇s disease（AD） patients preceding the presence of its clinical symptoms.Dysregulation of neuronalCa^2＋ will cause synaptic loss and neuronal death,eventually leading to memory impairments and cognitive decline.Treatments targetingCa^2＋ signaling pathways are potential therapeutic strategies against AD.The complicated interactions make it challenging and expensive to study the underlying mechanisms as to how Ca^2＋ signaling contributes to the pathogenesis of AD.Computational modeling offers new opportunities to study the signaling pathway and test proposed mechanisms.In this mini-review,we present some computational approaches that have been used to study Ca^2＋ dysregulation of AD by simulating Ca^2＋signaling at various levels.We also pointed out the future directions that computational modeling can be done in studying the Ca^2＋ dysregulation in AD.

A review of computational modeling and deep brain stimulation:applications to Parkinson’s disease

Biophysical computational models are complementary to experiments and theories,providing powerful tools for the study of neurological diseases.The focus of this review is the dynamic modeling and control strategies of Parkinson’s disease(PD).In previous studies,the development of parkinsonian network dynamics modeling has made great progress.Modeling mainly focuses on the cortex-thalamus-basal ganglia(CTBG)circuit and its sub-circuits,which helps to explore the dynamic behavior of the parkinsonian network,such as synchronization.Deep brain stimulation(DBS)is an effective strategy for the treatment of PD.At present,many studies are based on the side effects of the DBS.However,the translation from modeling results to clinical disease mitigation therapy still faces huge challenges.Here,we introduce the progress of DBS improvement.Its specific purpose is to develop novel DBS treatment methods,optimize the treatment effect of DBS for each patient,and focus on the study in closed-loop DBS.Our goal is to review the inspiration and insights gained by combining the system theory with these computational models to analyze neurodynamics and optimize DBS treatment.

Flow Field and Temperature Field in GaN-MOCVD Reactor Based on Computational Fluid Dynamics Modeling

Metal organic chenlical vapor deposition （AIOCVD） growth systems arc one of the. main types of equipment used for growing single crystal materials, such as GaN. To obtain fihn epitaxial materials with uniform performanee, the flow field and ternperature field in a GaN-MOCVD reactor are investigated by modeling and simulating. To make the simulation results more consistent with the actual situation, the gases in the reactor are considered to be compressible, making it possible to investigate the distributions of gas density and pressure in the reactor. The computational fluid dynamics method is used to stud,v the effects of inlet gas flow velocity, pressure in the reactor, rotational speed of graphite susceptor, and gases used in the growth, which has great guiding~ significance for the growth of GaN fihn materials.

NUMERICAL MODELING OF DUCTILE CRACK EXTENSION USING COMPUTATIONAL CELL ELEMENTS FOR WELDED JOINTS

A 3-D computationalframework was suggested to model stable growth of a macroscopic crack under model I condition. The Gurson-Tverpaaof dilatant plasticity model for voided materials describes the damage process. Fixed-sized, computational cell elements (containing voids) defined over a thin layer at the cmck plane simulate the ductile crack extension. Outside of this layer, the material remains undamaged by the void growth. The micro-mechanics parumeters controlling cmck growth are the thickness Of computational cell layen D, and the initial void porosity, fo. These parameters are calculated through analyses of ductile tearing to match R-curve obtained from testing of deep notch bend specimens for welded joints. The R-curve for the double edge notched tension specimens is eNctively predicted using these pammeters.The predicted R-curve gives a good agreement with the expemment results.

Modeling the effects of mechanical parameters on the hydrodynamic behavior of vertical current classifiers

This study modeled the effects of structural and dimensional manipulations on hydrodynamic behavior of a bench vertical current classifier. Computational fluid dynamics （CFD） approach was used as modeling method, and turbulent intensity and fluid velocity were applied as system responses to predict the over- flow cut size variations. These investigations showed that cut size would decrease by increasing diameter and height of the separation column and cone section depth, due to the decrease of turbulent intensity and fluid velocity. As the size of discharge gate increases, the overflow cut-size would decrease due to freely fluid stream out of the column. The overflow cut-size was significantly increased in downward fed classifier compared to that fed by upward fluid stream. In addition, reforming the shape of angular overflow outlet＇s weir into the curved form prevented stream inside returning and consequently unselec- tire cut-size decreasing.

Computational implementation of a GIS developed tool for prediction of dynamic ground movement and deformation due to underground extraction sequence

In the last century, there has been a significant development in the evaluation of methods to predict ground movement due to underground extraction. Some remarkable developments in three-dimensional computational methods have been supported in civil engineering, subsidence engineering and mining engineering practice. However, ground movement problem due to mining extraction sequence is effectively four dimensional （4D）. A rational prediction is getting more and more important for long-term underground mining planning. Hence, computer-based analytical methods that realistically simulate spatially distributed time-dependent ground movement process are needed for the reliable long-term underground mining planning to minimize the surface environmental damages. In this research, a new computational system is developed to simulate four-dimensional （4D） ground movement by combining a stochastic medium theory, Knothe time-delay model and geographic information system （GIS） technology. All the calculations are implemented by a computational program, in which the components of GIS are used to fulfill the spatial-temporal analysis model. In this paper a tight coupling strategy based on component object model of GIS technology is used to overcome the problems of complex three-dimensional extraction model and spatial data integration. Moreover, the implementation of computational of the interfaces of the developed tool is described. The GIS based developed tool is validated by two study cases. The developed computational tool and models are achieved within the GIS system so the effective and efficient calculation methodology can be obtained, so the simulation problems of 4D ground movement due to underground mining extraction sequence can be solved by implementation of the developed tool in GIS.

Computation of flow through the oesophagogastric junction

Whilst methods exist to indirectly measure the effects of increased flow or gastro-oesophageal refluxing, they cannot quantitatively measure the amount of acid travelling back up into the oesophagus during reflux, nor can they indicate the flow rate through the oesophagogastric junction (OGJ). Since OGJ dysfunction affects flow it seems most appropriate to describe the geometry of the OGJ and its effect on the flow. A device known as the functional lumen imaging probe (FLIP) has been shown to reliably measure the geometry of and pressure changes in the OGJ. FLIP cannot directly measure flow but the data gathered from the probe can be used to model flow through the junction by using computational flow dynamics (CFD). CFD uses a set of equations known as the Navier-Stokes equations to predict flow patterns and is a technique widely used in engineering. These equations are complex and require appropriate assumptions to provide simplifications before useful data can be obtained. With the assumption that the cross-sectional areas obtained via FLIP are circular, the radii of these circles can be obtained. A cubic interpolation scheme can then be applied to give a high-resolution geometry for the OGJ. In the case of modelling a reflux scenario, it can be seen that at the narrowest section a jet of fluid squirts into the oesophagus at a higher velocity than the fluid surrounding it. This jet has a maximum velocity of almost 2 ms-1 that occurs where the OGJ is at its narrowest. This simple prediction of acid ‘squirting’ into the oesophagusillustrates how the use of numerical methods can be used to develop a better understanding of the OGJ. This initial work using CFD shows some considerable promise for the future.

Numerical Simulation of Blood Flow in Aorta with Dilation:A Comparison between Laminar and LES Modeling Methods

Computational modeling methods have been increasingly employed to quantify aortic hemodynamic parameters that are challenging to in vivo measurements but important for the diagnosis/treatment of aortic disease.Although the presence of turbulence-like behaviors of blood flow in normal or diseased aorta has long been confirmed,the majority of existing computational model studies adopted the laminar flow assumption(LFA)in the treatment of sub-grid flow variables.So far,it remains unclear whether LFA would significantly compromise the reliability of hemodynamic simulation.In the present study,we addressed the issue in the context of a specific aortopathy,namely aortic dilation,which is usually accompanied by disturbed flow patterns.Three patient-specific aortas with treated/untreated dilation of the ascending segment were investigated,and their geometrical models were reconstructed from computed tomography angiographic images,with the boundary conditions being prescribed based on flow velocity information measured in vivo with the phase contrast magnetic resonance imaging technique.For the modeling of blood flow,apart from the traditional LFA-based method in which sub-grid flow dynamics is ignored,the large eddy simulation(LES)method capable of incorporating the dissipative energy loss induced by turbulent eddies at the sub-grid level,was adopted and taken as a reference for examining the performance of the LFA-based method.Obtained results showed that the simulated large-scale flow patterns with the two methods had high similarity,both agreeing well with in vivo measurements,although locally large between-method discrepancies in computed hemodynamic quantities existed in regions with high intensity of flow turbulence.Quantitatively,a switch from the LES to the LFAbased modeling method led to mild(<6%)changes in computed space-averaged wall shear stress metrics(i.e.,SA-TAWSS,SA-OSI)in the ascending aortic segment where intensive vortex evolution accompanied by high statistical Reynolds stress was observed.In addition,comparisons among the three aortas revealed that the treatment status of aortic dilation or the concomitant presence of aortic valve disease,despite its remarkable influence on flow patterns in the ascending aortic segment,did not significantly affect the degrees of discrepancies between the two modeling methods in predicting SA-TAWSS and SA-OSI.These findings suggest that aortic dilation per se does not induce strong flow turbulence that substantially negates the validity of LFA-based modeling,especially in simulating macro-scale hemodynamic features.

An In Vivo Experimental Validation of a Computational Model of Human Foot

Reliable computational foot models offer an alternative means to enhance knowledge on the biomechanics of human foot. Model validation is one of the most critical aspects of the entire foot modeling and analysis process.This paper presents an in vivo experiment combining motion capture system and plantar pressure measure platform to validate a three-dimensional finite element model of human foot.The Magnetic Resonance Imaging(MRI)slices for the foot modeling and the experimental data for validation were both collected from the same volunteer subject.The validated components included the comparison of static model predictions of plantar force,plantar pressure and foot surface deformation during six loading conditions,to equivalent measured data.During the whole experiment,foot surface deformation,plantar force and plantar pressure were recorded simultaneously during six different loaded standing conditions.The predictions of the current FE model were in good agreement with these experimental results.

CFD modeling and laboratory studies of dust cleaning efficacy of an efficient four stage non-clogging impingement filter for flooded-bed dust scrubbers

Fibrous-type flters are used to capture dust particles in mining and other occupations where personnel are exposed for prolonged periods.Dust cleansing devices including fooded-bed dust scrubbers use these mesh-type multi-layered flters.These flters trap dust particles efciently on their surface and inside their mesh.However,their continued operation leads to dust build-up and clogging.This results in increased resistance of the flter and lowered airfow rate through the scrubber.This could potentially enhance the exposure of the miners.A non-clogging self-cleaning impingement screen type dust flter was designed by the authors for use in mining and industrial dust cleansing applications.The flter guides dirt-laden air through rapidly turning paths which forces it to shed heavier particles.The particles impact one of the impermeable solid metallic flter surfaces and are removed from the airstream.A full cone water spray installed upstream prevents any surface buildup of dust.This paper summaried the computer models generated to show the flter operations and laboratory experiments including optical particle counting to establish the cleaning efciency.

Transformation from computation independent model to platform independent model with pattern

Model driven architecture(MDA) is an evolutionary step in software development.Model transformation forms a key part of MDA.The transformation from computation independent model(CIM) to platform independent model(PIM) is the first step of the transformation.This paper proposes an approach for this transformation with pattern.In this approach, we take advantage of"reuse"from various standpoints.Feature model is used to describe the requirement of the application.This can help us bring"reuse"into effect at requirement level.Moreover we use pattern to transform CIM to PIM.This can help us bring"reuse"into effect at development level.Meanwhile, pattern was divided into four hierarchies.Different hierarchies of pattern are used to help us utilize reuse at different phase of development.From another standpoint, feature model describes the problem of a domain while pattern describe the problem across domains.This can help us reuse the element in and across domains.Finally, the detailed process of the transformation is given.

Parallel Computation of Shallow-water Model on Workstations Cluster

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Evidence of Dual Scale Porous Mechanisms During Fluid Migration in Hardwood Species (Ⅱ) A Dual Scale Computational Model to Describe the Experimental Results

The second part of this paper is devoted to the computational modelling of transient water migration in hardwood. During re-saturation, the moisture content, measured during the process by using X-ray attenuation (see part 1 of this paper), increases quickly very close to the cavity, but requires a very long time for the remaining part of the sample to absorb the moisture in wetting. For this configuration and this material, the macroscopic approach fails. Consequently, a dual-porosity approach is proposed. The computational domain uses a 2-D axisymmetric configuration for which the axial coordinate represents the macroscopic longitudinal direction of the sample whereas the radial coordinate allows the slow migration from each active vessel towards the fibre zone to be considered. The latter is a microscopic space variable. The moisture content field evolution depicts clearly the dual scale mechanisms:a very fast longitudinal migration in the vessel followed by a slow migration from the vessel towards the fibre zone.The macroscopic moisture content field resulting from this dual scale mechanism is in quite good agreement with the experimental data.

Computational modelling of magnesium degradation in simulated body fluid under physiological conditions

Magnesium alloys are highly attractive for the use as temporary implant materials, due to their high biocompatibility and biodegradability.However, the prediction of the degradation rate of the implants is difficult, therefore, a large number of experiments are required. Computational modelling can aid in enabling the predictability, if sufficiently accurate models can be established. This work presents a generalized model of the degradation of pure magnesium in simulated body fluid over the course of 28 days considering uncertainty aspects. The model includes the computation of the metallic material thinning and is calibrated using the mean degradation depth of several experimental datasets simultaneously. Additionally, the formation and precipitation of relevant degradation products on the sample surface is modelled, based on the ionic composition of simulated body fluid. The computed mean degradation depth is in good agreement with the experimental data(NRMSE=0.07). However, the quality of the depth profile curves of the determined elemental weight percentage of the degradation products differs between elements(such as NRMSE=0.40 for phosphorus vs. NRMSE=1.03 for magnesium). This indicates that the implementation of precipitate formation may need further developments. The sensitivity analysis showed that the model parameters are correlated and which is related to the complexity and the high computational costs of the model. Overall, the model provides a correlating fit to the experimental data of pure Mg samples of different geometries degrading in simulated body fluid with reliable error estimation.

Pulse cleaning flow models and numerical computation of candle ceramic filters

Analytical and numerical computed models are developed for reverse pulse cleaning system of candle ceramic filters. A standard turbulent model is demonstrated suitably to the designing computation of reverse pulse cleaning system from the experimental and one dimensional computational result. The computed results can be used to guide the designing of reverse pulse cleaning system, which is optimum Venturi geometry. From the computed results, the general conclusions and the designing methods are obtained.

Computational model investigating the effect of magnetic field on neural–astrocyte microcircuit

Extremely low-frequency magnetic field is widely used as a noninvasive stimulation method in clinical practice and basic research. Electrical field induced from magnetic pulse can decrease or increase neuronal electrical activity. However, the cellular mechanism underlying the effects of magnetic field is not clear from experimental data. Recent studies have demonstrated that "non-neuronal" cells, especially astrocytes, may be the potential effector for transcranial magnetic stimulation(TMS). In the present study, we implemented a neural–astrocyte microcircuit computational model based on hippocampal architecture to investigate the biological effects of different magnetic field frequencies on cells. The purpose of the present study is to elucidate the main influencing factors of MS to allow a better understanding of its mechanisms.Our model reproduced the basic characteristics of the neuron and astrocyte response to different magnetic stimulation. The results predict that interneurons with lower firing thresholds were more active in magnetic fields by contrast to pyramidal neurons. And the synaptic coupling strength between the connected neurons may be one of the critical factor to affect the effect of magnetic field on cells. In addition, the simulations show that astrocytes can decrease or increase slow inward currents(SICs) to finely tune neuronal excitation, which suggests their key role in excitatory–inhibitory balance. The interaction between neurons and astrocytes may represent a novel target for effective therapeutic strategies involving magnetic stimulation.

A Computational Model for Pedestrian Level Wind Environment Around Tall Buildings

A computational model has been developed for the simulation of pedestrian level wind environment around tall buildings by coupling the numerical simulation of the full scale site and meteorological station materials. In the first step, the hybrid/mixed finite element method is employed to solve the two dimensional Navier Stokes equation for the flow field around tall buildings, in view of the influence of fluctuating wind, the flow field is revised with the effective wind velocity. The velocity ratio is defined in order to relate numerical wind velocity to oncoming reference wind velocity. In the second step, the frequency occurred discomfort wind velocity as a suitable criterion is calculated by use of the coupling between the numerical wind velocity and the wind velocity at the nearest meteorological station. The prediction accuracy of the wind environment simulation by use of the computation model will be discussed. Using the available wind data at the nearest meteorological station as well as the established criteria of wind discomfort, the frequency of wind discomfort can be predicted. A numerical example is given to illustrate the application of the proposed method.

Modeling the Social Reinforcement of Misinformation Dissemination on Social Media

Despite the salience of misinformation and its consequences, there still lies a tremendous gap in research on the broader tendencies in collective cognition that compels individuals to spread misinformation so excessively. This study examined social learning as an antecedent of engaging with misinformation online. Using data released by Twitter for academic research in 2018, Tweets that included URL news links of both known misinformation and reliable domains were analyzed. Lindström’s computational reinforcement learning model was adapted as an expression of social learning, where a Twitter user’s posting frequency of news links is dependent on the relative engagement they receive in consequence. The research found that those who shared misinformation were highly sensitive to social reward. Inflation of positive social feedback was associated with a decrease in posting latency, indicating that users that posted misinformation were strongly influenced by social learning. However, the posting frequency of authentic news sharers remained fixed, even after receiving an increase in relative and absolute engagement. The results identified social learning is a contributor to the spread of misinformation online. In addition, behavior driven by social validation suggests a positive correlation between posting frequency, gratification received from posting, and a growing mental health dependency on social media. Developing interventions for spreading misinformation online may profit by assessing which online environments amplify social learning, particularly the conditions under which misinformation proliferates.

Using computational fluid dynamic simulation with Flow-3D to reveal the origin of the mushroom stone in the Xiqiao Mountain of Guangdong, China

Mushroom shaped rocks are not uncommon in nature, but their origin is often misunderstood because they can be formed by different natural forces. A huge mushroom stone in a stream valley of the Xiqiao Mountain of Guangdong,China is widely believed to be formed through the way of stream water erosion. However, the result of the simulation performed with Flow-3 D in this study indicates that the mushroom shape of the rock could not have been sculpted by the flowing water erosion because the simulation result contradicts that of the field investigations:(1) the sediment brought by upstream flowing water tends to be deposited on the leeward side of the flowing water preventing the rock on this side form being eroded, but the narrowest part of the rock bottom is exactly located on this side of the rock and(2) the stream flow should erode the bed sediment and produce high abrasion on the rock surface on the upstream and lateral sides of the rock,respectively, but no abrasion marks are found on the same sides of the rock. Subsequent geological analyses in this study provide evidence that the narrow bottom of the mushroom stone was resulted from chemical and physical weathering happening within the sediment that used to deposit on the lee side of the stone.

ODE-Solver-Oriented Computational Method for the Structural Dynamic Analysis of Super Tall Buildings

The paper is to introduce a computational methodology that is based on ordinary differential equations （ODE） solver for the structural systems adopted by a super tall building in its preliminary design stage so as to facilitate the designers to adjust the dynamic properties of the adopted structural system. The construction of the study is composed by following aspects. The first aspect is the modelling of a structural system. As a typical example, a mega frame-core-tube structural system adopted by some famous super tall buildings such as Taipei 101 building, Shanghai World financial center, is employed to demonstrate the modelling of a computational model. The second aspect is the establishment of motion equations constituted by a group of ordinary differential equations for the analyses of free vibration and resonant response. The solutions of the motion equations （that constitutes the third aspect） resorted to ODE-solver technique. Finally, some valuable conclusions are summarized.