We develop a simple and efficient method for soft shadows from planar area light sources, based on explicit occlusion calculation by raytracing, followed by adaptive image-space filtering. Since the method is based on Monte Carlo sampling, it is accurate. Since the filtering is in image-space, it adds minimal overhead and can be performed at real-time frame rates. We obtain interactive speeds, using the Optix GPU raytracing framework. Our technical approach derives from recent work on frequency analysis and sheared pixellight filtering for offline soft shadows. While sample counts can be reduced dramatically, the sheared filtering step is slow, adding minutes of overhead. We develop the theoretical analysis to instead consider axis-aligned filtering, deriving the sampling rates and filter sizes. We also show how the filter size can be reduced as the number of samples increases, ensuring a consistent result that converges to ground truth as in standard Monte Carlo rendering.

SummaryInduced pluripotent stem cells (iPSCs) acquire embryonic stem cell (ESC)-like epigenetic states, including the X chromosome. Previous studies reported that human iPSCs retain the inactive X chromosome of parental cells, or acquire two active X chromosomes through reprogramming. Most studies investigated the X chromosome states in established human iPSC clones after completion of reprogramming. Thus, it is still not fully understood when and how the X chromosome reactivation occurs during reprogramming. Here, we report a dynamic change in the X chromosome state throughout reprogramming, with an initial robust reactivation of the inactive X chromosome followed by an inactivation upon generation of nascent iPSC clones. iPSCs with two active X chromosomes or an eroded X chromosome arise in passaging iPSCs. These data provide important insights into the plasticity of the X chromosome of human female iPSCs and will be crucial for the future application of such cells in cell therapy and X-linked disease modeling.

a) 1-bounce indirect lighting, Our Method average 63 samples per pixel (spp) (b) Adaptive Sampling and Filtering (c) unfiltered 63 spp adaptively sampled (d) unfiltered 63 spp uniformly sampled (e) Our Method 63 adap. sample, filter (f) Equal error 324 spp Figure 1: (a) We render the Sponza Atrium with 262K triangles, textures and 1-bounce physically-based global illumination at about 2 fps on an NVIDIA GTX 690 graphics card, with an average of 63 Monte Carlo (adaptive) samples per pixel (spp) raytraced on the GPU with Optix, followed by adaptive image filtering. (b) Adaptive sampling rates and filter widths (in pixels) derived from our novel frequency analysis of indirect illumination. (c) Insets of the unfiltered result. Adaptive sampling produces lower noise in high-frequency regions with small filter sizes (see right of bottom inset), with greater noise in low-frequency regions, that will be filtered out. Compare to (d) uniform standard stratified Monte Carlo sampling with uniformly distributed noise. Our method (e) after adaptive sampling and filtering is accurate at 63spp. (f) Equal error at 324 spp, which is still noisy. Overhead in our algorithm is minimal, and we provide a speedup vs equal error of 5×. Readers are encouraged to zoom into the PDF for this and all subsequent figures, to more clearly see the noise and image quality. AbstractWe introduce an algorithm for interactive rendering of physicallybased global illumination, based on a novel frequency analysis of indirect lighting. Our method combines adaptive sampling by Monte Carlo ray or path tracing, using a standard GPU-accelerated raytracer, with real-time reconstruction of the resulting noisy images. Our theoretical analysis assumes diffuse indirect lighting, with general Lambertian and specular receivers. In practice, we demonstrate accurate interactive global illumination with diffuse and moderately glossy objects, at 1-3 fps. We show mathematically that indirect illumination is a structured signal in the Fourier domain, with inherent band-limiting due to the BRDF and geometry terms. We extend previous work on sheared and axis-aligned filtering for motion blur and shadows, to develop an image-space filtering method for interreflections. Our method enables 5−8× reduced sampling rates and wall clock times, and converges to ground truth as more samples are added. To develop our theory, we overcome important technical challenges-unlike previous work, there is no light source to serve as a band-limit in indirect lighting, and we also consider non-parallel geometry of receiver and reflecting surfaces, without first-order approximations.

Spatially charting molecular cell types at single-cell resolution across the three-dimensional (3D) volume of the brain is critical for illustrating the molecular basis of the brain anatomy and functions. Single-cell RNA sequencing (scRNA-seq) has profiled molecular cell types in the mouse brain, but cannot capture their spatial organization. Here, we employed an in situ sequencing technique, STARmap PLUS, to map more than one million high-quality cells across the whole adult mouse brain and the spinal cord, profiling 1,022 genes at subcellular resolution with a voxel size of 194 X 194 X 345 nm in 3D. We developed computational pipelines to segment, cluster, and annotate molecularly defined cell types and tissue regions with single-cell resolution. To create a transcriptome-wide spatial atlas, we further integrated the STARmap PLUS measurements with a published scRNA-seq atlas, imputing 11,844 genes at the single-cell level. Finally, we engineered a highly expressed RNA barcoding system to delineate the tropism of a brain-wide transgene delivery tool, AAV-PHP.eB, revealing its single-cell resolved transduction efficiency across the molecular cell types and tissue regions of the whole mouse brain. Together, our datasets and annotations provide a comprehensive, high-resolution single-cell resource that integrates spatial molecular atlas, cell taxonomy, brain anatomy, and genetic manipulation accessibility of the mammalian central nervous system (CNS).