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.

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.

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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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.

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.

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.

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.

Agricultural Policy Simulation Based on Computable General Equilibrium Model

[Objective] This study aimed to examine the simulated effect of Computable General Equilibrium （CGE）-based agricultural policy simulation system. [Method] The policy simulation platform based on CGE model was constructed by integrating policy simulation, CGE model and Decision Supporting System （DSS）. The scenario analysis method was used to analyze the agricultural subsides policy simulation through empirical analysis. [Result] Farmers were the main beneficiaries of increasing agricultural production subsidies, which increased farmers＇ income and improved the export of agriculture products. The prototype system could solve the problems in actual policy simulation. [Conclusion] The results lay the foundation for the quantitative study on agricultural subsidy policy in China.

Development of multiple soft computing models for estimating organic and inorganic constituents in coal

The distribution of the various organic and inorganic constituents and their influences on the combustion of coal has been comprehensively studied.However,the combustion characteristics of pulverized coal depend not only on rank but also on the composition,distribution,and combination of the macerals.Unlike the proximate and ultimate analyses,determining the macerals in coal involves the use of sophisticated microscopic instrumentation and expertise.In this study,an attempt was made to predict the amount of macerals(vitrinite,inertinite,and liptinite)and total mineral matter from the Witbank Coalfields samples using the multiple input single output white-box artificial neural network(MISOWB-ANN),gene expression programming(GEP),multiple linear regression(MLR),and multiple nonlinear regression(MNLR).The predictive models obtained from the multiple soft computing models adopted are contrasted with one another using difference,efficiency,and composite statistical indicators to examine the appropriateness of the models.The MISOWB-ANN provides a more reliable predictive model than the other three models with the lowest difference and highest efficiency and composite statistical indicators.

Gastrointestinal tract modelling in health and disease

The gastrointestinal (GI) tract is the system of organs within multi-cellular animals that takes in food, digests it to extract energy and nutrients, and expels the remaining waste. The various patterns of GI tract function are generated by the integrated behaviour of multiple tissues and cell types. A thorough study of the GI tract requires understanding of the interactions between cells, tissues and gastrointestinal organs in health and disease. This depends on knowledge, not only of numerous cellular ionic current mechanisms and signal transduction pathways, but also of large scale GI tissue structures and the special distribution of the nervous network. A unique way of coping with this explosion in complexity is mathematical and computational modelling; providing a computational framework for the multilevel modelling and simulation of the human gastrointestinal anatomy and physiology. The aim of this review is to describe the current status of biomechanical modelling work of the GI tract in humans and animals, which can be further used to integrate the physiological, anatomical and medical knowledge of the GI system. Such modelling will aid research and ensure that medical professionals benefit, through the provision of relevant and precise information about the patient's condition and GI remodelling in animal disease models. It will also improve the accuracy and efficiency of medical procedures, which could result in reduced cost for diagnosis and treatment.

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.

Cancer models in preclinical research:A chronicle review of advancement in effective cancer research

Cancer is a major stress for public well-being and is the most dreadful disease.The models used in the discovery of cancer treatment are continuously changing and extending toward advanced preclinical studies.Cancer models are either naturally existing or artificially prepared experimental systems that show similar features with human tumors though the heterogeneous nature of the tumor is very familiar.The choice of the most fitting model to best reflect the given tumor system is one of the real difficulties for cancer examination.Therefore,vast studies have been conducted on the cancer models for developing a better understanding of cancer invasion,progression,and early detection.These models give an insight into cancer etiology,molecular basis,host tumor interaction,the role of microenvironment,and tumor heterogeneity in tumor metastasis.These models are also used to predict novel can-cer markers,targeted therapies,and are extremely helpful in drug development.In this review,the potential of cancer models to be used as a platform for drug screening and therapeutic discoveries are highlighted.Although none of the cancer models is regarded as ideal because each is associated with essential caveats that restraint its application yet by bridging the gap between preliminary cancer research and transla-tional medicine.However,they promise a brighter future for cancer treatment.

A Unified Framework of the Cloud Computing Service Model

After a comprehensive literature review and analysis, a unified cloud computing framework is proposed, which comprises MapReduce, a vertual machine, Hadoop distributed file system （HDFS）, Hbase, Hadoop, and virtualization. This study also compares Microsoft, Trend Micro, and the proposed unified cloud computing architecture to show that the proposed unified framework of the cloud computing service model is comprehensive and appropriate for the current complexities of businesses. The findings of this study can contribute to the knowledge for academics and practitioners to understand, assess, and analyze a cloud computing service application.

Intensity Allocation Criteria of Carbon Emissions Permits and Regional Economic Development in China——Based on a 30-Province/Autonomous Region Computable General Equilibrium Model

The intensity allocation criteria of carbon emissions permits and its influence on China＇s regional development are analyzed through the 30-province/autonomous region computable general equilibrium （CGE） model. Simulation results show that： industrial intensity criteria without taking regional economic development into account deepen the unbalance of regional economic development; regional intensity criteria without taking industrial properties into account exert little negative impact on regional harmonious development, but relatively high negative influence on high-carbon emission industries. The two-step allocation scheme that the central government allocates emissions permits to provincial governments based on regional economic development and then provincial governments allocate emissions permits to emission resources or entities based on industrial properties is a feasible and operable choice.

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.