CG Model Research Articles

MinActionPath2: path generation between different conformations of large macromolecular assemblies by action minimization.

Recent progress in solving macromolecular structures and assemblies by cryogenic electron microscopy techniques enables sampling of their conformations in different states that are relevant to their biological function. Knowing the transition path between these conformations would provide new avenues for drug discovery. While the experimental study of transition paths is intrinsically difficult, in-silico methods can be used to generate an initial guess for those paths. The Elastic Network Model (ENM), along with a coarse-grained representation (CG) of the structures are among the most popular models to explore such possible paths. Here we propose an update to our software platform MinActionPath that generates non-linear transition paths based on ENM and CG models, using action minimization to solve the equations of motion. The new website enables the study of large structures such as ribosomes or entire virus envelopes. It provides direct visualization of the trajectories along with quantitative analyses of their behaviors at http://dynstr.pasteur.fr/servers/minactionpath/minactionpath2_submission.

Single particle conversion of woody biomass using fully-resolved and Euler–Lagrange coarse-graining approaches

The conversion of woody biomass is studied by means of a layer-based model for thermally-thick biomass particles (Thunman et al. 2002, Ström et al. 2013). The model implementation is successfully validated against experiments that study particle conversion in a drop tube reactor. After this validation step, this work focuses on the well-known problem of grid dependence of two-phase numerical simulations using the standard Euler–Lagrange (EL) framework. This issue is addressed and quantified by comparing EL data that models the particle boundary layers to corresponding simulations which fully resolve these boundary layers (fully-resolved, FR, simulations). A comparison methodology for the conceptually different FR and EL approaches by extracting the heat transfer coefficient from the detailed FR simulations is proposed and confirms that the EL results are strongly grid-dependent. This issue is overcome by applying a set of coarse-graining methods for the EL framework. Two coarse-graining methods are evaluated, a previously suggested diffusion-based method (DBM) and a new approach based on moving averages referred to as MAM. It is shown that both DBM and MAM can successfully recover the detailed FR data for pure particle heating for a case where the grid size is half the particle diameter, i.e. when the standard EL method fails. Both coarse-graining methods also give improved results for an EL simulation that considers the more complex combined physics of particle heating, drying and devolatilisation, given that the CG model parameters that scale the corresponding CG interaction volumes are sufficiently large. Based on the available FR data, recommended model parameter ranges for DBM and MAM are provided as a function of normalised boundary layer thickness. The novel MAM approach is shown to be significantly more efficient than the DBM and therefore suitable for future EL simulations with multiple particles.

Coarse-Grained Molecular Dynamics Simulations of Organic Friction Modifier Adsorption on Rough Surfaces under Shear

Reducing friction energy losses is crucial in mechanical systems, often achieved through lubrication strategies employing friction modifiers. These additives adsorb onto surfaces, forming boundary film to prevent solid–solid contacts. However, atomistic simulation techniques used to study these additives often ignore surface roughness due to high computational cost. This study addresses this gap by employing Coarse-Grained Molecular Dynamics (CG MD) to investigate the impact of surface roughness on the adsorption of Organic Friction Modifiers (OFMs) under shear. Traditional self-diffusion methods prove inadequate for determining the damping coefficients in CG models because of strong OFM adsorption effects. Therefore, shear-induced motion is introduced for the coefficient determination. The simulation reveals that a symmetrical model (identical opposing surfaces) shows OFM slip, desorption, and re-adsorption trends on rough surfaces, while an asymmetrical model (smooth cylinder on a flat surface) demonstrates increased adsorption on rough flat surfaces (up to 60.9%) compared to smooth flat surfaces under similar shearing conditions. However, rough flat surfaces with a smaller wavelength (6 nm) exhibit faster OFM desorption along the asperity region, up to four times more than a 24 nm wavelength surface. This research emphasizes the importance of considering surface roughness in simulating OFM behavior for lubrication applications.

An Accurate and Transferable Coarse-Graining Method for the Investigation of Microscopic Fracture Behaviors of Epoxy Thermosets.

Coarse-grained modeling shows potential in exploring the thermo-mechanical behaviors of polymers applied in harsh conditions such as cryogenic environment, but its accuracy in simulating fracture behaviors of highly cross-linked epoxy thermosets is largely limited due to the complex molecular structures of the cross-linked networks. We address this fundamental problem by developing a CG modeling method where the backbones and electrostatic interaction (EI) contributions in the cross-linked networks are retained, and thus the potentials of the CG model can be directly extracted, or parametrized on the basis of, existing all-atomistic (AA) force fields. A multilevel parametrization procedure was adopted, where the bond potentials were parametrized relying on the results of density functional theory (DFT) simulation, whereas the nonbond potentials were parametrized by renormalizing the cohesive interaction strength. Remarkably, the CG model can reproduce stress-strain responses highly consistent with the AA simulation results at multiple stages, including elastic deformation, yielding, plastic flow, strain hardening, etc., and the straightforward parametrization procedure can be easily transferred to different materials and thermodynamic conditions. The CG modeling method was then used to build a large-scale representative volume element (RVE) to investigate the microscopic fracture behavior of an epoxy thermoset. It has been discovered that EI contributions play a significant role in generating correct mechanical responses and fracture morphologies. The influences of temperature (i.e., from room to cryogenic temperatures) and strain rates were discussed, and the fracture morphology in the RVE was unveiled and analyzed in a quantitative manner.

Fostering University-Industry Collaboration: Unveiling the Mediating Influence of Gratitude between Relational Benefits and Relationship Value

The relationship between universities and industry (UIRs) has been a significant phenomenon for the past decade. The West has made tremendous progress in this area since the Industrial Revolution. However, there is a need for more reliable studies on UIRs, specifically on the creation of value, which can help identify gaps in this field. This research's primary objective is to analyze gratitude's role in understanding the relationship between relational benefits (RB) and relationship value (RV). To achieve this, a survey questionnaire was used to assess the applicability of the CG model to the field of education. The results indicate that CG mediates the relationship between relationship benefits and relational value.

OpenMSCG: A Software Tool for Bottom-Up Coarse-Graining.

The "bottom-up" approach to coarse-graining, for building accurate and efficient computational models to simulate large-scale and complex phenomena and processes, is an important approach in computational chemistry, biophysics, and materials science. As one example, the Multiscale Coarse-Graining (MS-CG) approach to developing CG models can be rigorously derived using statistical mechanics applied to fine-grained, i.e., all-atom simulation data for a given system. Under a number of circumstances, a systematic procedure, such as MS-CG modeling, is particularly valuable. Here, we present the development of the OpenMSCG software, a modularized open-source software that provides a collection of successful and widely applied bottom-up CG methods, including Boltzmann Inversion (BI), Force-Matching (FM), Ultra-Coarse-Graining (UCG), Relative Entropy Minimization (REM), Essential Dynamics Coarse-Graining (EDCG), and Heterogeneous Elastic Network Modeling (HeteroENM). OpenMSCG is a high-performance and comprehensive toolset that can be used to derive CG models from large-scale fine-grained simulation data in file formats from common molecular dynamics (MD) software packages, such as GROMACS, LAMMPS, and NAMD. OpenMSCG is modularized in the Python programming framework, which allows users to create and customize modeling "recipes" for reproducible results, thus greatly improving the reliability, reproducibility, and sharing of bottom-up CG models and their applications.

Characterizing Protein-Protein Interactions and Viscosity of a Monoclonal Antibody from Low to High Concentration Using Small-Angle X-ray Scattering and Molecular Dynamics Simulations.

Understanding protein-protein interactions and formation of reversible oligomers (clusters) in concentrated monoclonal antibody (mAb) solutions is necessary for designing stable, low viscosity (η) concentrated formulations for processing and subcutaneous injection. Here we characterize the strength (K) of short-range anisotropic attractions (SRA) for 75-200 mg/mL mAb2 solutions at different pH and cosolute conditions by analyzing structure factors (Seff(q)) from small-angle X-ray scattering (SAXS) using coarse-grained molecular dynamics simulations. Best fit simulations additionally provide cluster size distributions, fractal dimensions, cluster occluded volume, and mAb coordination numbers. These equilibrium properties are utilized in a model to account for increases in viscosity caused by occluded volume in the clusters (packing effects) and dissipation of stress across lubricated fractal clusters. Seff(q) is highly sensitive to K at 75 mg/mL where mAbs can mutually align to form SRA contacts but becomes less sensitive at 200 mg/mL as steric repulsion due to packing becomes dominant. In contrast, η at 200 mg/mL is highly sensitive to SRA and the average cluster size from SAXS/simulation, which is observed to track the cluster relaxation time from shear thinning. By analyzing the distribution of sub-bead hot spots on the 3D mAb surface, we identify a strongly attractive hydrophobic patch in the complementarity determining region (CDR) at pH 4.5 that contributes to the high K and consequently large cluster sizes and high η. Adding NaCl screens electrostatic interactions and increases the impact of hydrophobic attraction on cluster size and raises η, whereas nonspecific binding of Arg attenuates all SRA, reducing η. The hydrophobic patch is absent at higher pH values, leading to smaller K, smaller clusters, and lower η. This work constitutes a first attempt to use SAXS and CG modeling to link both structural and rheological properties of concentrated mAb solutions to the energetics of specific hydrophobic patches on mAb surfaces. As such, our work opens an avenue for future research, including the possibility of designing coarse-grained models with physically meaningful interacting hot spots.

Author Correction to “Mesoscale Simulation of Vesiculation of Lipid Droplets”

We regret to announce that two parameters (θ0, rc) were found incorrect after publication due to the author’s typing errors. The two parameters were published in Chin. J. Chem. Phys. 27, 663–671 (2014). DOI: https://doi.org/10.1063/1674-0068/27/06/663-671. In page 664, in the sentence “Similarly, a small equilibrium angle (θ0 = 10°) with the bending constant (kangle = 20 kJ/(mol·rad2)) is empirically selected to stabilize the bilayer structure.”, “θ0 = 10°” should be corrected as “θ0 = 30°”. In page 665, in the sentence “In the present CG model rc is set as 2.772 nm and the start position of r1 = 2.25 nm.”, “rc is set as 2.772 nm” should be corrected as “rc is set as 2.722 nm”. The two parameters (θ0, rc) of the model used in the work are the same as those of the work [J. Phys. Chem. B 120, 2262–2270 (2016)].

Understanding the graphene-polymer interfacial mechanical behavior via coarse-grained modeling

Understanding the interfacial behavior of graphene-polymer nanocomposite is a long-standing endeavor to gain deep insight into the mechanical properties of engineered structural materials. In this study, we implement the ‘hard’ cutoff scheme to develop a 4-1 mapping coarse-grained graphene (CGGr) model and the corresponding CG potential TersoffCG(4-1), which faithfully reproduces the honeycomb structure (bond length and angle) and mechanical properties of the graphene sheet compared to experimental results. Taking the poly(methyl methacrylate) (PMMA) and graphene sheet as a representative composite system, we establish a predictive CG modeling framework to study the interfacial behavior at a molecular level. By performing the rate-dependent interfacial separation simulations, our results reveal that lower separation velocity and thicker flexible layer can facilitate the craze fibrils formation and further enhance the toughness of the composite, which attribute to the adequate response of polymer to the graphene under lower velocity and more polymers that potentially to form fibrils under thicker flexible layer. Our work demonstrates the efficacy of TersoffCG(4-1) potential in understanding the interfacial mechanical behavior of graphene-polymer nanocomposite, offering an effective modeling strategy for performance improvement by designing the interfaces.

GB1 Dimerization in Crowders: A Multiple Resolution Approach.

In-cell protein-protein association, which is crucial in enzyme catalysis and polymerization, occurs in an environment that is highly heterogeneous and crowded. The crowder molecules exclude the reactant molecules from occupying certain regions of the cell, resulting in changes in the reaction thermodynamics and kinetics. Recent studies, both experiment and simulations, revealed that the nature of the interaction between crowder and protein species, in particular the soft interactions, plays an important role in crowder induced effects on protein association. To this end, from a simulation perspective, it is important to decipher the level of structural resolution in a protein-crowder model that can faithfully capture the influence of crowding on protein association. Here, we investigate the dimerization of model system GB1 in the presence of lysozyme crowders at two structural resolutions. The lower resolution model assumes both protein and crowder species as spherical beads, similar to the analytical scaled particle theory model, whereas the higher resolution model retains residue specific structural details for protein and crowder species. From the higher resolution model, it is found that GB1 dimer formation is destabilized in the presence of lysozyme crowders, and the destabilization is more for the side-by-side dimer compared to the domain-swapped dimer, in qualitative agreement with experimental findings. However, the low resolution CG model predicts stabilization of the dimers in the presence of the lysozyme crowder, similar to the SPT model. Our results indicate a nontrivial role of the choice of model resolution in computer simulation studies investigating crowder induced effects.

A coarse-grain reactive model of RDX: Molecular resolution at the μm scale.

Predictive models for the thermal, chemical, and mechanical response of high explosives at extreme conditions are important for investigating their performance and safety. We introduce a particle-based, reactive model of 1,3,5-trinitro-1,3,5-triazinane (RDX) with molecular resolution utilizing generalized energy-conserving dissipative particle dynamics with reactions. The model is parameterized with respect to the data from atomistic molecular dynamics simulations as well as from quantum mechanical calculations, thus bridging atomic processes to the mesoscales, including microstructures and defects. It accurately captures the response of RDX under a range of thermal loading conditions compared to atomistic simulations. In addition, the Hugoniot response of the CG model in the overdriven regime reasonably matches atomistic simulations and experiments. Exploiting the model's high computational efficiency, we investigate mesoscale systems involving millions of molecules and characterize size-dependent criticality of hotspots in RDX. The combination of accuracy and computational efficiency of our reactive model provides a tool for investigation of mesoscale phenomena, such as the role of microstructures and defects in the shock-to-deflagration transition, through particle-based simulation.

Topical Calendula officinalis L. inhibits inflammatory pain through antioxidant, anti-inflammatory and peripheral opioid mechanisms

ObjectiveThe present study evaluated the antinociceptive activity of Calendula officinalis L. (Ca) cream on inflammatory hypernociception. MethodsCreams with different Ca concentrations were tested for their ability to ameliorate pain-related behavior and edema in rats using formalin test, carrageenan (Cg)-induced acute inflammation model, bradykinin (BK)-induced acute inflammation model, and complete Freund’s adjuvant (CFA)-induced chronic inflammation model. Using the formalin test, we also examined the implication of peripheral opioid receptors in the antinociceptive mechanisms of Ca cream, by means of Q-naloxone, a peripherally acting nonselective opioid antagonist. Furthermore, the effects of Ca cream compared with diclofenac on BK-induced edema were examined when the kininase II in tissue was preserved or inhibited by captopril. The local production of redox biomarkers in formalin model, tumor necrosis factor-α (TNF-α) in Cg model and histopathological changes in CFA model were also evaluated. ResultsA single application of Ca cream at a dose of 10% or 30% (w/w) decreased the formalin-induced licking/biting behavior during both phases of this test in a Q-naloxone-sensitive manner. This effect was associated with the reduction of oxidative stress in the injured paw and the edema associated with the later phase of formalin-induced pain. A single application of Ca cream (10% or 30%) reduced paw edema and thermal hypernociception in Cg-induced acute inflammation, corresponding with a local decrease in TNF-α. Ca cream also inhibited BK-induced spontaneous nociceptive behavior and paw inflammation in both paradigms studied. Repeated applications of Ca cream also decreased CFA-induced chronic inflammation, mechanical hypernociception and histopathological changes in the paw. ConclusionThese results reveal the topical antinociceptive and antiedematogenic effects of Ca cream. A modulatory action on peripheral opioid receptors associated with its antioxidant mechanism may be involved, at least in part, in its analgesic effects. These findings may have an impact on the clinical management of painful inflammatory diseases.

Development and verification of coarse‐grain CFD‐DEM for nonspherical particles in a gas–solid fluidized bed

AbstractComputational fluid dynamics coupled with discrete element method (CFD‐DEM) has been widely used to understand the complicated fundamentals inside gas–solid fluidized beds. To realize large‐scale simulations, CFD‐DEM integrated with coarse‐grain model (CG CFD‐DEM) provides a feasible solution, and has led to a recent upsurge of interest. However, when dealing with large‐scale simulations involving irregular‐shaped particles such as biomass particles featuring elongated shapes, current CG models cannot function as normal because they are all developed for spherical particles. To address this issue, a CG CFD‐DEM for nonspherical particles is proposed in this study, and the morphology of particles is characterized by the super‐ellipsoid model. The effectiveness and accuracy of CG CFD‐DEM for nonspherical particles are comprehensively evaluated by comparing the hydrodynamic behaviors with the results predicted by traditional CFD‐DEM in a gas–solid fluidized bed. It is demonstrated that the proposed model can accurately model gas–solid flow containing nonspherical particles, merely the particle dynamics are somewhat lost due to the scaleup of particle size. Finally, the calculation efficiency of CG CFD‐DEM is assessed, and the results show that CG CFD‐DEM can largely reduce computational costs mainly by improving the calculation efficiency of DEM. In general, the proposed CG CFD‐DEM for nonspherical particles strikes a good balance between efficiency and accuracy, and has shown its prospect as a high‐efficiency alternative to traditional CFD‐DEM for engineering applications involving nonspherical particles.

Revisiting Chaplygin gas cosmologies with the recent observations of high-redshift quasars

In this paper, we use the latest observations of quasars covering the redshift range of 0.04<z<5.1 to investigate a series of Chaplygin gas models as candidates for unified dark matter and dark energy. Based on different combinations of available standard candle and standard ruler data, we put constraints on the generalized Chaplygin gas (GCG), modified Chaplygin gas (MCG), new generalized Chaplygin gas (NGCG) and viscous generalized Chaplygin gas (VGCG) models. Moreover, we apply Jensen–Shannon divergence (JSD), statefinder diagnostics, and the deviance information criterion (DIC) to distinguish these CG models, based on the statistical results derived from Markov chain Monte Carlo method. The results show that (1) The standard ruler data could provide more stringent constraints on the cosmological parameters of different CG models considered in this analysis. Interestingly, the matter density parameter varOmega _{m} and Hubble constant H_{0} derived from the available data are well consistent with those from the Planck 2018 results; (2) Based on the statistical criteria JSD, our findings demonstrate the well consistency between Chaplygin gas and the concordance varLambda CDM model. However, in the framework of statefinder diagnostics, the GCG and NGCG models cannot be distinguished from varLambda CDM, while MCG and VGCG models show significant deviation from varLambda CDM in the present epoch; (3) According to the the statistical criteria DIC, we show that the MCG and VGCG models have substantial observational support from high-redshift quasars, whereas the GCG and NGCG models miss out on the less observational support category but can not be ruled out.

UNIFICATION OF CORPORATE GOVERNANCE (CG) MODEL IN THE EUROPEAN UNION AND BREXIT: AN ANALYTICAL VIEW

The aim of this research is to explore the necessity of a uniform corporate governance (model for the EU region. It attempts to examine the current challenges as well as the current CG paradigm. This study focuses on identifying the actions taken to implement CG reforms in the EU region. It identifies the problems that businesses face as a result of the lack of appropriate legislation. This book covers the experts' perspectives on the harmonization of the CG structure, both for and against. It examines the post-Brexit environment for company structures, focusing on the EU and the UK. This research explores and highlights the future of Brexit and CG procedures. The research comprises of the two section. The first section discusses the characteristics of the CG model and its unified framework. This is an important aspect of the question. It includes information on unified CG such as its definition, sources, types, key features, historical reform initiatives and expert commentary on the coherent and coordinated legal framework for CG in the European region. The last section explores the role of Brexit in CG in the EU. This section also includes some analytical lines on the effects of Brexit on future corporate operations and investor organisations. Keywords: Unification, corporate governance, EU, Brexit.

Fragmentation Size Distribution Measurement by GNSS-Aided Photogrammetry at Real Mine Site

In mining operations that employ explosives and mineral processing, one of the important factors for efficient and low-cost operation is the fragmentation size distribution of rock after it has been blasted. Automatic scaling is a critical component of fragmentation size distribution measurement as it will directly determine the accuracy of the size estimation. In this study, we propose a method to create a system for creating a scaled 3D CG model, without the use of ground truth data such as GCPs (Ground Control Points), for the purpose of improving fragmentation size distribution measurement using positional data such as GNSS (Global Navigation Satellite System)-aided photogrammetry. We confirmed the validation of the method through an experimental evaluation of actual muckpiles. The results showed evidence of improving the scaling aspect of 3D fragmentation measurement systems without using GCPs or manual scales, specifically in surface mines where GNSS data are available.

A study of linguistic manipulations of activating, seeking and creating common ground in intercultural business communication

Abstract Previous studies on common ground (CG, for short) have mainly focused on its definition and functions in various daily interactions. Few studies explore the linguistic manipulations of CG in cross-cultural business interactions. This paper aims to fill in this gap by examining how sellers and buyers manipulate linguistic actions of activating, seeking and creating CG to make a deal. This study instantiates and develops Kecskes’ (2013) CG model. Based on qualitative analysis of data collected from email interactions between Chinese sellers and Australian buyers, I find that (1) Interlocutors often activate their core CG through manipulating frequency markers such as “again”, and epistemic markers such as “I knew”, “you know”, “might”; (2) Interlocutors seek core CG and emergent CG by manipulating epistemic markers such as “I’m sure”; (3) Interlocutors often bring the third party or element into the communication to create emergent CG by using question markers such as “you see?”, imperative markers such as “Do you understand!”, and narrative markers like “I tell you” and “once” or “before”; (4) The interpersonal manipulations of CG construction contribute to business integrity and reliability because the more efforts interlocutors make to activate, seek, and create CG, the more clarified and acceptable their business relations become in business communication. For the purpose of validating what I have found, I conduct a quantitative study of linguistic means of constructing CG in the Santa Barbara Corpus of Spoken American English (SBCSAE), and summarize the typical linguistic means of activating, seeking, and creating CG in various settings.

Cooperative antimicrobial action of melittin on lipid membranes: A coarse-grained molecular dynamics study

We conducted a series of coarse-grained molecular dynamics (CG-MD) simulations to investigate the complicated actions of melittin, which is an antimicrobial peptide (AMP) derived from honey bee venom, on a lipid membrane. To accurately simulate the AMP action, we developed and used a protein CG model as an extension of the pSPICA force field (FF), which was designed to reproduce several thermodynamic quantities and structural properties. At a low peptide-to-lipid (P/L) ratio (1/102), no defect was detected. At P/L = 1/51, toroidal pore formation was observed due to collective insertion of multiple melittin peptides from the N-termini. The pore formation was initiated by a local increase in membrane curvature in the vicinity of the peptide aggregate. At a higher P/L ratio (1/26), two more modes were detected, seemingly not controlled by the P/L ratio but by a local arrangement of melittin peptides: 1. Pore formation accompanied by lipid extraction by melittin peptides:a detergent-like mechanism. 2. A rapidly formed large pore in a significantly curved membrane: bursting. Thus, we observed three pore formation modes (toroidal pore formation, lipid extraction, and bursting) depending on the peptide concentration and local arrangement. These observations were consistent with experimental observations and hypothesized melittin modes. Through this study, we found that the local arrangements and population of melittin peptides and the area expansion rate by membrane deformation were key to the initiation of and competition among the multiple pore formation mechanisms.

Effectiveness of rastall gravity in modified chaplygin gas inspired viscous-flation

This paper is a contribution to study the effectiveness of Rastall gravity (RG) by another mechanism of warm viscous inflation inspired by modified Chaplygin gas (MCG). The matter contents of our cosmos are taken to be standard scalar field (ϕ) and radiation within flat FRW geometry. We establish the current model using intermediate form of scale factor and calculate the analytic solution of inflaton, effective potential V(ϕ) necessary to inflate the Universe and entropy density S under slow-roll limit. The further work in this paper is restricted to high dissipative regime, taking constant and variable dissipative (Γ) and viscous coefficients (ξ). The evaluated exact solutions are the main source in developing the inflationary observable like scalar/tensor power spectra, scalar/tensor spectral indices, tensor to scalar ratio and running of scalar spectral index for our model. The model parameters as well as additional theory parameter λ are constrained to check the compatibility of RG with Planck 2018 data via and α s − n s trajectories. We conclude that RG along with modification of CG model can lead to significant changes in the early universe.

Development of AR training systems for Humanitude dementia care

This paper presents a comparative study of two AR training systems for Humanitude dementia care. Humanitude is a multimodal comprehensive care methodology for patients with dementia and has attracted considerable attention as a gentle and effective care technique. To provide an effective training system for Humanitude, we developed HEARTS 1, which realizes simultaneous sensing and interaction by combining a real training entity and augmented reality technology. However, training experiments using HEARTS 1 indicated that HEARTS 1 had certain weaknesses that should be addressed, namely, the usability of the AR display or the impression of the CG model. This paper presents a new prototype called HEARTS 2 consisting of Microsoft HoloLens 2 as well as realistic and animated CG models of older women. Psychological experiments were conducted to identify the difference in the usability of the AR displays, such as the weight and the field of view, and the impression of the CG models. We also conducted questionnaire surveys for beginners and medical professionals and preliminary training experiments to evaluate the usefulness of HEARTS 2. Based on the psychological experiments and questionnaire surveys, we concluded that HEARTS 2 was more comfortable and suitable for a training system for dementia care.