Spatial genetic structure and seed quality of a southernmost Abies nephrolepis population.

Abies nephrolepis (Trautv. ex Maxim.) Maxim. has its southernmost populations in South Korea and they are expected to decline under climate change. To establish a strategic conservation plan, this study aimed to investigate the spatial genetic structure and seed characteristics of A. nephrolepis. We used nine microsatellite markers on 165 individuals of A. nephrolepis and sampled seeds in a southernmost population at Mt. Hambaeksan, South Korea. We observed a high level of heterozygosity, and a simulation study found that sampling 20 individuals was enough to secure sufficient genetic diversity on average. Spatial autocorrelation analysis revealed that individuals had a positive genetic relationship until 30 m. Bayesian clustering models, STRUCTURE and GENELAND, failed to achieve a consensus in the optimal number of population (K), estimating K = 1 and K = 2, respectively. Principal coordinate analysis supported the absence of genetic substructure within the study population. There was a large variance in seed production among mother trees. On average, seeds of A. nephrolepis from Mt. Hambaeksan had a purity of 70.4% and a germination percentage of 32.2%. We found that seed weight was the most effective indicator of seed quality. Mother trees at higher altitudes had poorer purity which is threatening to A. nephrolepis considering the upslope retreat of subalpine species under climate change. Our results provide insights into the interactions among spatial processes, genetic structure, and seed quality within a population of A. nephrolepis.

Geometry image super-resolution with AnisoCBConvNet architecture for efficient cloth modeling.

We propose an anisotropic constrained-boundary convolutional neural networks (hereafter, AnisoCBConvNet) that can stably express high-quality meshes without oscillation by applying super-resolution operations to low-resolution cloth meshes. As a training set for the neural network, we use a pair between simulation data of low resolution (LR) cloth and data obtained by applying the same simulation to high resolution (HR) cloth with increased quad mesh resolution of LR cloth. The actual data used for training are 2D geometry images converted from 3D meshes. The proposed AnisoCBConvNet is used to train an image synthesizer that converts LR geometry images to HR geometry images. In particular, by controlling the weights anisotropically near the boundary, the problem of surface wrinkling caused by oscillation is alleviated. When the HR geometry image obtained through AnisoCBConvNet is converted back to the HR cloth mesh, details including wrinkles are expressed better than the input cloth mesh. In addition, our results improved the noise problem in the existing geometry image approach. We tested AnisoCBConvNet-based super-resolution in various simulation scenarios, and confirmed stable and efficient performance in most of the results. By using our method, it will be possible to effectively produce CG VFX created using high-quality cloth simulation in games and movies.

Hydrodynamic microfabrication via"on the fly" photopolymerization of microscale fibers and tubes.

A microfluidic apparatus capable of creating continuous microscale cylindrical polymeric structures has been developed. This system is able to produce microstructures (e.g. fibers, tubes) by employing 3D multiple stream laminar flow and "on the fly"in-situ photopolymerization. The details of the fabrication process and the characterization of the produced microfibers are described. The apparatus is constructed by merging pulled glass pipettes with PDMS molding technology and used to manufacture the fibers and tubes. By controlling the sample and sheath volume flow rates, the dimensions of the microstructures produced can be altered without re-tooling. The fiber properties including elasticity, stimuli responsiveness, and biosensing are characterized. Responsive woven fabric and biosensing fibers are demonstrated. The fabrication process is simple, cost effective and flexible in materials, geometries, and scales.