Multi-view Inverse Rendering for Large-scale Real-world Indoor Scenes

We present a multi-view inverse rendering method for large-scale real-world indoor scenes that reconstructs global illumination and physically-reasonable SVBRDFs. Unlike previous representations, where the global illumination of large scenes is simplified as multiple environment maps, we propose a compact representation called Texture-based Lighting (TBL). It consists of 3D meshs and HDR textures, and efficiently models direct and infinite-bounce indirect lighting of the entire large scene. Based on TBL, we further propose a hybrid lighting representation with precomputed irradiance, which significantly improves the efficiency and alleviate the rendering noise in the material optimization. To physically disentangle the ambiguity between materials, we propose a three-stage material optimization strategy based on the priors of semantic segmentation and room segmentation. Extensive experiments show that the proposed method outperforms the state-of-the-arts quantitatively and qualitatively, and enables physically-reasonable mixed-reality applications such as material editing, editable novel view synthesis and relighting. The project page is at https://lzleejean.github.io/TexIR.Comment: The project page is at: https://lzleejean.github.io/TexI

Emerging Nonvolatile Memories to Go Beyond Scaling Limits of Conventional CMOS Nanodevices

Continuous dimensional scaling of the CMOS technology, along with its cost reduction, has rendered Flash memory as one of the most promising nonvolatile memory candidates during the last decade. With the Flash memory technology inevitably approaching its fundamental limits, more advanced storage nanodevices, which can probably overcome the scaling limits of Flash memory, are being explored, bringing about a series of new paradigms such as FeRAM, MRAM, PCRAM, and ReRAM. These devices have indeed exhibited better scaling capability than Flash memory while also facing their respective physical drawbacks. The consequent tradeoffs therefore drive the information storage device technology towards further advancement; as a result, new types of nonvolatile memories, including carbon memory, Mott memory, macromolecular memory, and molecular memory have been proposed. In this paper, the nanomaterials used for these four emerging types of memories and the physical principles behind the writing and reading methods in each case are discussed, along with their respective merits and drawbacks when compared with conventional nonvolatile memories. The potential applications of each technology are also briefly assessed

Induction of PD-L1 expression by epidermal growth factor receptor–mediated signaling in esophageal squamous cell carcinoma

PURPOSE: The purpose of this study was to investigate the potential effect of activation of epidermal growth factor receptor (EGFR) signaling pathway on the expression of programmed death-ligand 1 (PD-L1) in esophageal squamous cell carcinoma (ESCC) cells with EGFR overexpression. METHODS: Flow cytometry and Western blot methods were used to assess PD-L1 expression on ESCC cells when EGFR signaling pathway was activated by epidermal growth factor (EGF) with or without EGFR-specific inhibitor AG-1478, and then EGFR signaling array was applied to analyze the potential signaling pathways involved. RESULTS: This study found that PD-L1 expression increased significantly in an EGFR-dependent manner by the activation of EGFR signaling and decreased sharply when EGFR signaling was blocked. The upregulated expression of PD-L1 was not associated with EGFR-STAT3 signaling pathway, but may be affected by EGFR–PI3K–AKT, EGFR–Ras–Raf–Erk, and EGR–PLC-γ signaling pathways. CONCLUSION: The expression of PD-L1 can be regulated by EGFR signaling activation in ESCC, which indicates an important role for EGFR-mediated immune escape and potential molecular pathways for EGFR-targeted therapy and immunotherapy