MPI-Flow: Learning Realistic Optical Flow with Multiplane Images

The accuracy of learning-based optical flow estimation models heavily relies on the realism of the training datasets. Current approaches for generating such datasets either employ synthetic data or generate images with limited realism. However, the domain gap of these data with real-world scenes constrains the generalization of the trained model to real-world applications. To address this issue, we investigate generating realistic optical flow datasets from real-world images. Firstly, to generate highly realistic new images, we construct a layered depth representation, known as multiplane images (MPI), from single-view images. This allows us to generate novel view images that are highly realistic. To generate optical flow maps that correspond accurately to the new image, we calculate the optical flows of each plane using the camera matrix and plane depths. We then project these layered optical flows into the output optical flow map with volume rendering. Secondly, to ensure the realism of motion, we present an independent object motion module that can separate the camera and dynamic object motion in MPI. This module addresses the deficiency in MPI-based single-view methods, where optical flow is generated only by camera motion and does not account for any object movement. We additionally devise a depth-aware inpainting module to merge new images with dynamic objects and address unnatural motion occlusions. We show the superior performance of our method through extensive experiments on real-world datasets. Moreover, our approach achieves state-of-the-art performance in both unsupervised and supervised training of learning-based models. The code will be made publicly available at: \url{https://github.com/Sharpiless/MPI-Flow}.Comment: Accepted to ICCV202

Regularities in simple sequence repeat variations induced by a cross of resynthesized Brassica napus and natural Brassica napus

Interspecific hybridization can induce extensive variation in genome sequences, including simple sequence repeat (SSR) regions. To determine the characteristics of SSR variation induced by interspecific hybridization and the possible effect of SSR variation on gene function, we constructed a Brassica napus doubled-haploid (DH) population from a cross between natural B. napus and resynthesized B. napus (B. oleracea × B. rapa) and identified, located, sequenced and functionally annotated SSR variants.The results showed that novel SSR variants were generated in the F generation and maintained in the introgressed DH population. Elimination of sequences carrying SSRs also occurred in the F hybrids, with three times as many sequences lost in the introgressed DH population compared to in the F hybrids, probably due to non-homologous recombination. The degree of SSR variation observed depended primarily on the number of SSR repeats and secondarily on the nucleotide composition of the SSR motifs.In the introgressed DH population, many genes containing SSRs exhibited frameshift mutations (62.5%) due to the expansion or contraction of the SSR motifs following deletion deletion (25%) or insertion (12.5%) mutations.Most genes harboring SSR variants were associated with vital metabolic processes, such as protein or DNA metabolic processes. The SSR variation induced by interspecific hybridization reflects an intrinsic property of species adaptability post-hybridization through variation. This study is beneficial to understanding the origin of SSRs and the effects of SSR mutation on polyploid genomes

Behind every domain there is a shift: adapting distortion-aware vision transformers for panoramic semantic segmentation

In this paper, we address panoramic semantic segmentation which is under-explored due to two critical challenges: (1) image distortions and object deformations on panoramas; (2) lack of semantic annotations in the 360◦ imagery. To tackle these problems, first, we propose the upgraded Transformer for Panoramic Semantic Segmentation, i.e., Trans4PASS+, equipped with Deformable Patch Embedding (DPE) and Deformable MLP (DMLPv2) modules for handling object deformations and image distortions whenever (before or after adaptation) and wherever (shallow or deep levels). Second, we enhance the Mutual Prototypical Adaptation (MPA) strategy via pseudo-label rectification for unsupervised domain adaptive panoramic segmentation. Third, aside from Pinhole-to-Panoramic (PIN2PAN) adaptation, we create a new dataset (SynPASS) with 9,080 panoramic images, facilitating Synthetic-to-Real (SYN2REAL) adaptation scheme in 360◦ imagery. Extensive experiments are conducted, which cover indoor and outdoor scenarios, and each of them is investigated with PIN2PAN and SYN2REAL regimens. Trans4PASS+ achieves state-of-the-art performances on four domain adaptive panoramic semantic segmentation benchmarks. Code is available at https://github.com/jamycheung/Trans4PASS

Behind Every Domain There is a Shift: Adapting Distortion-aware Vision Transformers for Panoramic Semantic Segmentation

In this paper, we address panoramic semantic segmentation which is under-explored due to two critical challenges: (1) image distortions and object deformations on panoramas; (2) lack of semantic annotations in the 360-degree imagery. To tackle these problems, first, we propose the upgraded Transformer for Panoramic Semantic Segmentation, i.e., Trans4PASS+, equipped with Deformable Patch Embedding (DPE) and Deformable MLP (DMLPv2) modules for handling object deformations and image distortions whenever (before or after adaptation) and wherever (shallow or deep levels). Second, we enhance the Mutual Prototypical Adaptation (MPA) strategy via pseudo-label rectification for unsupervised domain adaptive panoramic segmentation. Third, aside from Pinhole-to-Panoramic (Pin2Pan) adaptation, we create a new dataset (SynPASS) with 9,080 panoramic images, facilitating Synthetic-to-Real (Syn2Real) adaptation scheme in 360-degree imagery. Extensive experiments are conducted, which cover indoor and outdoor scenarios, and each of them is investigated with Pin2Pan and Syn2Real regimens. Trans4PASS+ achieves state-of-the-art performances on four domain adaptive panoramic semantic segmentation benchmarks. Code is available at https://github.com/jamycheung/Trans4PASS.Comment: Extended version of CVPR 2022 paper arXiv:2203.01452. Code is available at https://github.com/jamycheung/Trans4PAS

Protective Effects of Hydrogen against Low-Dose Long-Term Radiation-Induced Damage to the Behavioral Performances, Hematopoietic System, Genital System, and Splenic Lymphocytes in Mice

Molecular hydrogen (H2) has been previously reported playing an important role in ameliorating damage caused by acute radiation. In this study, we investigated the effects of H2 on the alterations induced by low-dose long-term radiation (LDLTR). All the mice in hydrogen-treated or radiation-only groups received 0.1 Gy, 0.5 Gy, 1.0 Gy, and 2.0 Gy whole-body gamma radiation, respectively. After the last time of radiation exposure, all the mice were employed for the determination of the body mass (BM) observation, forced swim test (FST), the open field test (OFT), the chromosome aberration (CA), the peripheral blood cells parameters analysis, the sperm abnormality (SA), the lymphocyte transformation test (LTT), and the histopathological studies. And significant differences between the treatment group and the radiation-only groups were observed, showing that H2 could diminish the detriment induced by LDLTR and suggesting the protective efficacy of H2 in multiple systems in mice against LDLTR

Tailoring the surface of perovskite through in situ growth of Ru/RuO2 nanoparticles as robust symmetrical electrodes for reversible solid oxide cells

Although numerous perovskite oxides can enhance the electrochemical activity via exsolved metallic nanoparticles on the surface, most of them can only be applied as catalysts in a reducing atmosphere. These nanoparticles cause serious performance degradation in oxidizing conditions due to the formation of low-conductive metal oxides. This poses a big challenge to the design of highly active catalysts of electrochemical devices, especially for symmetrical solid oxide cells. Herein, based on the strategy of exsolved metallic nanoparticles in A-site deficient perovskite, a unique and simple method is demonstrated for the synthesis of Ru/RuO2 nanoparticles on the surface of perovskite oxide via in situ growth. The electrode material (La0.75Sr0.25)0.9Cr0.5Mn0.45Ru0.05O3−δ (LSCMR) is designed through careful choice of composition and the core idea is to make use of the exsolved nanoparticles concept applied for the first time at both hydrogen electrode and oxygen electrode for symmetrical solid oxide cells. Inspired by exsolved Ru and RuO2, the surface-decorated LSCMR exhibits significantly enhanced electrochemical activity for both H2 and O2, respectively, accompanied by high redox long-term stability. Moreover, simple, low-cost, and environmental-friendly synthesis of Ru/RuO2 nanoparticles on the substrate of typical perovskites is realized with this in situ growth approach

Sample multiplexing-based targeted pathway proteomics with real-time analytics reveals the impact of genetic variation on protein expression.

Targeted proteomics enables hypothesis-driven research by measuring the cellular expression of protein cohorts related by function, disease, or class after perturbation. Here, we present a pathway-centric approach and an assay builder resource for targeting entire pathways of up to 200 proteins selected from \u3e10,000 expressed proteins to directly measure their abundances, exploiting sample multiplexing to increase throughput by 16-fold. The strategy, termed GoDig, requires only a single-shot LC-MS analysis, ~1 µg combined peptide material, a list of up to 200 proteins, and real-time analytics to trigger simultaneous quantification of up to 16 samples for hundreds of analytes. We apply GoDig to quantify the impact of genetic variation on protein expression in mice fed a high-fat diet. We create several GoDig assays to quantify the expression of multiple protein families (kinases, lipid metabolism- and lipid droplet-associated proteins) across 480 fully-genotyped Diversity Outbred mice, revealing protein quantitative trait loci and establishing potential linkages between specific proteins and lipid homeostasis

The efficacy and prognosis analysis after stereotactic body radiotherapy for multiple primary early-stage lung cancer

Background and purpose: More and more patients with multiple primary early-stage lung cancer are choosing to receive stereotactic body radiation therapy (SBRT), and this study aimed to retrospectively analyze the efficacy and prognostic factors of SBRT. Methods: In this study, patients who underwent SBRT at Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine from August 2014 to December 2020 and who met the inclusion criteria were included. Patients with multiple primary early-stage lung cancer were examined for efficacy and prognostic factors. After using propensity score matching (PSM), the difference in efficacy of SBRT between single and multiple primary early-stage lung cancer was observed. Results: This study included 241 early-stage lung cancer patients with SBRT, including 94 patients with multiple primary early-stage lung cancer. The 3- and 5-year local control rate (LC), progression-free survival (PFS) and overall survival (OS) were 87.1% and 71.3%, 84.0% and 66.9%, 93.3% and 79.3% in multiple primary early-stage lung cancer, respectively. Patients with multiple primary early-stage lung cancer did not experience any grade 3 or higher pulmonary toxicity with an overall toxicity incidence of 54.3%, and grade 2 toxicity occurred in 24 patients (25.5%). There was a total of 18 (19.1%) recurrences, and there were 3 (3.2%), 1 (1.1%), 12 (12.7%) and 2 (2.1%) patients with multiple primary early-stage lung cancers who experienced local recurrence, regional recurrence, distant metastasis and uncertain death, respectively. Patients with multiple primary early-stage lung cancer and those with single primary early-stage lung cancer had significant differences in clinical features prior to PSM. After PSM, there were 56 patients with multiple primary early-stage lung cancer and 56 patients with single primary early-stage lung cancer, and there was no statistically significant difference in LC (P = 0.291), PFS (P = 0.954) and OS (P = 0.880). Age≥70 years was an independent risk factor for OS of multiple primary early-stage lung cancer, according to an analysis of the prognostic variables of SBRT in 94 patients with multiple primary early-stage lung cancer. Regarding synchronous (≤180 d) and metachronous (>180 d) multiple primary early-stage lung cancer, there was no discernible difference between the two groups (P = 0.440). There was no significant difference in the total number of treatments for multiple primary early-stage lung cancer (P = 0.232) and no significant difference in the type of treatment for multiple primary early-stage lung cancer (P = 0.225) among 59 patients with synchronous multiple primary early-stage lung cancer within 5 years of the first-to-last treatment interval. Conclusion: SBRT has a strong and comparable efficacy for multiple primary early-stage lung cancer compared with single primary early-stage lung cancer, making it a viable treatment choice. Based on age and tumor biological behavior of the lesion, future strategies and procedures for local intervention of multiple primary early-stage lung cancer need to be investigated