Emission and focusing characteristics of volcano-structured double-gated field emitter arrays

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The Role of the Ventromedial Prefrontal Cortex in Preferential Decisions for Own- and Other-Age Faces

Own-age bias is a well-known bias reflecting the effects of age, and its role has been demonstrated, particularly, in face recognition. However, it remains unclear whether an own-age bias exists in facial impression formation. In the present study, we used three datasets from two published and one unpublished functional magnetic resonance imaging (fMRI) study that employed the same pleasantness rating task with fMRI scanning and preferential choice task after the fMRI to investigate whether healthy young and older participants showed own-age effects in face preference. Specifically, we employed a drift-diffusion model to elaborate the existence of own-age bias in the processes of preferential choice. The behavioral results showed higher rating scores and higher drift rate for young faces than for older faces, regardless of the ages of participants. We identified a young-age effect, but not an own-age effect. Neuroimaging results from aggregation analysis of the three datasets suggest a possibility that the ventromedial prefrontal cortex (vmPFC) was associated with evidence accumulation of own-age faces; however, no clear evidence was provided. Importantly, we found no age-related decline in the responsiveness of the vmPFC to subjective pleasantness of faces, and both young and older participants showed a contribution of the vmPFC to the parametric representation of the subjective value of face and functional coupling between the vmPFC and ventral visual area, which reflects face preference. These results suggest that the preferential choice of face is less susceptible to the own-age bias across the lifespan of individuals

CFD Benchmark Tests for Indoor Environmental Problems: Part 1 Isothermal/Non-Isothermal Flow in 2D and 3D Room Model

Commercially available Computational Fluid Dynamics (CFD) software have been applied in indoor environmental design in recent years, but the prediction accuracy depends on an understanding of fluid dynamics fundamentals, in setting appropriate boundary and numerical conditions. This study aims to provide practical modelling information related to prediction accuracy and problematic areas in CFD applications in air conditioning and ventilation, through a series of benchmark tests and reported the results. Six commercial CFD codes were evaluated while two benchmark test cases were performed on isothermal/non-isothermal flow in 2D and 3D room models. The influence of mesh design, and turbulence models showed that using a standard k-ε model on a coarse mesh could provide sufficiently accurate results for practical purposes, by reducing the relaxation coefficient. Evaluation using different CFD programs on a non-isothermal room airflow showed different performances in predicting temperature distributions. The OpenFOAM code showed the closest matching results between three codes tests

CFD Benchmark Tests for Indoor Environmental Problems: Part 1 Isothermal/Non-Isothermal Flow in 2D and 3D Room Model

Commercially available Computational Fluid Dynamics (CFD) software have been applied in indoor environmental design in recent years, but the prediction accuracy depends on an understanding of fluid dynamics fundamentals, in setting appropriate boundary and numerical conditions. This study aims to provide practical modelling information related to prediction accuracy and problematic areas in CFD applications in air conditioning and ventilation, through a series of benchmark tests and reported the results. Six commercial CFD codes were evaluated while two benchmark test cases were performed on isothermal/non-isothermal flow in 2D and 3D room models. The influence of mesh design, and turbulence models showed that using a standard k-ε model on a coarse mesh could provide sufficiently accurate results for practical purposes, by reducing the relaxation coefficient. Evaluation using different CFD programs on a non-isothermal room airflow showed different performances in predicting temperature distributions. The OpenFOAM code showed the closest matching results between three codes tests

CFD Benchmark Tests for Indoor Environmental Problems: Part 4 Air-conditioning Airflows, Residential Kitchen Airflows and Fire-Induced Flow

Computational Fluid Dynamics (CFD) has become practical design tool for indoor environment recent years and the application cases have been increasing. Though the improvement of the prediction accuracy of CFD is needed in connection with the upgrade of design quality in indoor environment and Heating, Ventilation and air-conditioning (HVAC) system, the prediction accuracy of CFD simulation depends on the understanding for the fundamentals of fluid dynamics and the setting of appropriate boundary and numerical conditions as well. Additionally, deeper understanding to a specific problem regarding indoor environment is also required. The series of this study aimed to provide with the practical information such as prediction accuracy and problematic areas related to CFD applications in air conditioning and ventilation, then performed benchmark tests and reported the results. Especially in this Part 4, benchmark test results for Air-conditioning airflows, Residential kitchen airflows and Fire-induced flow were introduced and discussed

CFD Benchmark Tests for Indoor Environmental Problems: Part 2 Cross-Ventilation Airflows and Floor Heating Systems

Commercial Computational Fluid Dynamics (CFD) software is practically applied in indoor environmental design recent years but the prediction accuracy of CFD simulation depends on the understanding for the fundamentals of fluid dynamics and the setting of appropriate boundary and numerical conditions as well. Additionally, deeper understanding to a specific problem regarding indoor environment is also requested. The series of this study aimed to provide with the practical information such as prediction accuracy and problematic areas related to CFD applications in indoor environment, air conditioning and ventilation, then performed benchmark tests and reported the results. In this Part 2, benchmark test results for cross-ventilation airflows and floor heating systems were introduced. The highest reproducibility of the predicted results compared with the wind tunnel results occurred when the Z0-type wall function was used as the floor-surface boundary condition and the SST k–ω for the turbulence model in case of cross-ventilation flow and SST k–ω model showed also the closest matching results with experiment in case of natural convection in a room with floor heating