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INTRODUCTION: The postacute sequelae of COVID-19 (PASC) is a serious heterogeneous condition that affects a significant minority of those who endured COVID-19. PASC involves multiple body systems and an illness trajectory that has stages now being identified in medical research. OBJECTIVE: Traditional Chinese Medicine (TCM) and acupuncture are well suited to conceptualize and treat PASC and other postviral conditions. No description of TCM theory and its relationship with modern medical theory about PASC and its illness trajectory currently exists. CONCLUSION: The authors provide an overview of the potential value of TCM for conceptualizing and treating PASC with a few examples and clarify directions for research.

We introduce a fast joint optimization of unit cells across the whole metasur-face, exploiting interactions between nearby cells to produce a desired near-field profile and improving whole-lens focusing efficiency.

A novel deep learning neural network architecture is proposed to predict the near electrical field produced by metasurface devices with long-distance coupling effects in large neighborhoods of nano-pillars. This reduces LPA-FDTD error by 60%.

It is not widely appreciated that freeform irradiance tailoring can produce irradiance patterns with sharply resolved features from extended light sources. However, conservation of étendue limits the amount of high frequency content, i.e., edges, that can be achieved in the irradiance pattern. We provide upper and lower bounds on the number of distinct sharp irradiance features that can be resolved from a thick freeform lens of unknown shape, and on the lens size needed to achieve a desired level of detail.

We show how to correct an optical surface to transform an arbitrary incident light field into a desired irradiance pattern on a projection surface. Beam dilation errors and optical surface corrections are derived from the pullbacks of the actual and desired irradiances. Etendue effects — the principal obstacle to extended-source tailoring — are factored out by solving a sparse linear system. The method accommodates nontrivial projection surfaces, transport phenomena, and incident wavefronts, including those from multiple extended light sources. Numerical experiments achieve high fidelity and contrast ratios in as little as O(Nlog N)-time for a surface represented by N height values.

In this article, we consider the design of a compact freeform optical surface that uniformly irradiates an arbitrary convex polygonal region from an extended light source, while controlling spill. This problem has attracted a large body of literature that has primarily covered highly symmetric special cases or cases where the solution is approximated by a zero-étendue design based on a point source. Practical versions of this illumination design problem will likely feature large asymmetric light-emitting diodes, compact lenses, and irregular targets on angled projection surfaces. For these settings, we develop a solution method based on an edge ray mapping that routes maximally off-axis rays from the edges of the source through the edge of the optic to the edges of the target polygon. This determines the sag and normals along the boundary of the freeform surface. A “spill-free” surface is then interpolated from the boundary information and optimized to uniformize the irradiance, while preserving the polygonal boundary. Highly uniform irradiances (relative standard deviation < .01 ) can be attained with good control of spill, even when the exit surface is less than three source diameters from the embedded source.

We present a generative model for isotropic bidirectional reflectance distribution functions (BRDFs) based on acquired reflectance data. Instead of using analytical reflectance models, we represent each BRDF as a dense set of measurements. This allows us to interpolate and extrapolate in the space of acquired BRDFs to create new BRDFs. We treat each acquired BRDF as a single high-dimensional vector taken from a space of all possible BRDFs. We apply both linear (subspace) and non-linear (manifold) dimensionality reduction tools in an effort to discover a lower-dimensional representation that characterizes our measurements. We let users define perceptually meaningful parametrization directions to navigate in the reduced-dimension BRDF space. On the low-dimensional manifold, movement along these directions produces novel but valid BRDFs.