QMNet: Importance-Aware Message Exchange for Decentralized Multi-Agent Reinforcement Learning

To improve the performance of multi-agent reinforcement learning under the constraint of wireless resources, we propose a message importance metric and design an importance-aware scheduling policy to effectively exchange messages. The key insight is spending the precious communication resources on important messages. The message importance depends not only on the messages themselves, but also on the needs of agents who receive them. Accordingly, we propose a query-message-based architecture, called QMNet. Agents generate queries and messages with the environment observation. Sharing queries can help calculate message importance. Exchanging messages can help agents cooperate better. Besides, we exploit the message importance to deal with random access collisions in decentralized systems. Furthermore, a message prediction mechanism is proposed to compensate for messages that are not transmitted. Finally, we evaluate the proposed schemes in a traffic junction environment, where only a fraction of agents can send messages due to limited wireless resources. Results show that QMNet can extract valuable information to guarantee the system performance even when only $30\%$ of agents can share messages. By exploiting message prediction, the system can further save $40\%$ of wireless resources. The importance-aware decentralized multi-access mechanism can effectively avoid collisions, achieving almost the same performance as centralized scheduling

Short Tandem Repeat Profiles In Ovarian Carcinoma Cells During Primary Culture

Purpose Cell authentication is a necessary procedure to avoid scientific data from cell culture experiments with cross-contamination or false classification. A genetic fingerprint pattern of a specimen by short tandem repeats (STR) is self-evident. Due to high amount of chromosomal rearrangements, known in epithelia ovary cancer cells and the instable STR pattern described in other tumour entities like leukaemia, this study explores the suitability of STR profiling for primary cultured epithelial ovary cancer cells. Methods STR profiles of epithelial ovary cancers of 16 patients were compared with corresponding blood and corresponding primary cell cultures. The primary cell cultures of epithelial ovary tumours were passaged up to 28 times. In between, cultures were cryo conserved and recultured again, two to five times per patient. Results In two cases, the STR pattern of tumour lost alleles (1/16 and 3/16) in comparison of corresponding STR-pattern from blood. In comparison to blood, cell culture of a third case, lost four alleles (4/16) accompanied with morphologic changes after 14th passage. It is equal after cryo conservation of the seventh passage from the same patient. The only changes in STR profiles we recognized are losses of alleles. Remaining STR markers allow authentication. Conclusions Very likely, the allelic drop-outs beyond passage 14 assume complex genetic losses of heterozygosis resulting in changed growth behaviour of cells. All other STR-profiles of remaining 15 patients analysed in this study are stable over all passages and freeze–thaw processes. Thus, ovary cancer cell cultures in research should be authenticated by STR-profile in general

Effective Real Image Editing with Accelerated Iterative Diffusion Inversion

Despite all recent progress, it is still challenging to edit and manipulate natural images with modern generative models. When using Generative Adversarial Network (GAN), one major hurdle is in the inversion process mapping a real image to its corresponding noise vector in the latent space, since its necessary to be able to reconstruct an image to edit its contents. Likewise for Denoising Diffusion Implicit Models (DDIM), the linearization assumption in each inversion step makes the whole deterministic inversion process unreliable. Existing approaches that have tackled the problem of inversion stability often incur in significant trade-offs in computational efficiency. In this work we propose an Accelerated Iterative Diffusion Inversion method, dubbed AIDI, that significantly improves reconstruction accuracy with minimal additional overhead in space and time complexity. By using a novel blended guidance technique, we show that effective results can be obtained on a large range of image editing tasks without large classifier-free guidance in inversion. Furthermore, when compared with other diffusion inversion based works, our proposed process is shown to be more robust for fast image editing in the 10 and 20 diffusion steps' regimes.Comment: Accepted to ICCV 2023 (Oral

HollowNeRF: Pruning Hashgrid-Based NeRFs with Trainable Collision Mitigation

Neural radiance fields (NeRF) have garnered significant attention, with recent works such as Instant-NGP accelerating NeRF training and evaluation through a combination of hashgrid-based positional encoding and neural networks. However, effectively leveraging the spatial sparsity of 3D scenes remains a challenge. To cull away unnecessary regions of the feature grid, existing solutions rely on prior knowledge of object shape or periodically estimate object shape during training by repeated model evaluations, which are costly and wasteful. To address this issue, we propose HollowNeRF, a novel compression solution for hashgrid-based NeRF which automatically sparsifies the feature grid during the training phase. Instead of directly compressing dense features, HollowNeRF trains a coarse 3D saliency mask that guides efficient feature pruning, and employs an alternating direction method of multipliers (ADMM) pruner to sparsify the 3D saliency mask during training. By exploiting the sparsity in the 3D scene to redistribute hash collisions, HollowNeRF improves rendering quality while using a fraction of the parameters of comparable state-of-the-art solutions, leading to a better cost-accuracy trade-off. Our method delivers comparable rendering quality to Instant-NGP, while utilizing just 31% of the parameters. In addition, our solution can achieve a PSNR accuracy gain of up to 1dB using only 56% of the parameters.Comment: Accepted to ICCV 202

Vascular endothelial growth factor-B gene transfer exacerbates retinal and choroidal neovascularization and vasopermeability without promoting inflammation

The role of vascular endothelial growth factor (VEGF)-B in the eye is poorly understood. The present study was conducted to evaluate the effect of overexpression of VEGF-B via adeno-associated virus (AAV) gene transfer on ocular angiogenesis, inflammation, and the blood-retinal barrier (BRB).Three recombinant AAV vectors were prepared, expressing the 167 (AAV-VEGF-B167) or 186 amino acid isoform (AAV-VEGF-B186) of VEGF-B or the green fluorescent protein (GFP) reporter gene (AAV-GFP). Approximately 1 x 10\u2079 viral genome copies of AAV-VEGF-B167, AAV-VEGF-B186, or AAV-GFP were intraocularly injected. The efficacy of the gene transfer was assessed by directly observing GFP, by immunohistochemistry, or by real-time PCR. A leukostasis assay using fluorescein isothiocyanate-conjugated Concanavalin A was used to evaluate inflammation. The BRB was assessed using a quantitative assay with \ub3H-mannitol as a tracer. Retinal neovascularization (NV) was assessed at postnatal day 17 in oxygen-induced ischemic retinopathy after intravitreal injection of AAV-VEGF-B in left eyes and AAV-GFP in right eyes at postnatal day 7. Two weeks after injection of AAV vectors, choroidal NV was generated by laser photocoagulation and assessed 2 weeks later.GFP expression was clearly demonstrated, primarily in the retinal pigment epithelium (RPE) and outer retina, 1-6 weeks after delivery. mRNA expression levels of VEGF-B167 and VEGF-B186 were 5.8 and 12 fold higher in the AAV-VEGF-B167- and AAV-VEGF-B186-treated groups, respectively. There was no evidence of an inflammatory response or vessel abnormality following injection of the vectors in normal mice; however, VEGF-B increased retinal and choroidal neovascularization. AAV-VEGF-B186, but not AAV-VEGF-B167, enhanced retinal vascular permeability.VEGF-B overexpression promoted pathological retinal and choroidal NV and BRB breakdown without causing inflammation, which is associated with the progression of diabetic retinopathy and age-related macular degeneration, showing that these complications are not dependent on inflammation. VEGF-B targeting could benefit antiangiogenic therapy

Can prophylactic transvaginal cervical cerclage improve pregnancy outcome in patients receiving cervical conization? A meta-analysis

Objectives: Cervical conization could increase the risk of cervical insufficiency. This study systematically evaluated the value of prophylactic transvaginal cervical cerclage following cervical conization with regards to pregnancy outcome. Material and methods: We performed a systematic review of the literature, using Web of Science, and Embase, the published time ranged from the date that database established to December 2019. Pregnant patients, who had a previous history of cervical conization for CIN or early cervical cancer, were enrolled. Two researchers searched these databases and estimated the included studies' quality independently, depending on the same criteria. Results: Our meta-analysis is incorporate 3560 cases eventually. Meta-analysis showed that when compared to the no-cerclage group, the risk ratio (RR) of preterm birth in the prophylactic transvaginal cervical cerclage group was 1.85 [95% confidence interval [CI]: 1.22–2.80; p = 0.004); the RR of premature rupture of membranes was 1.5 (95% CI: 1.17–1.93; p = 0.001). Conclusions: The rates of preterm birth were significantly higher in women following cervical conization with transvaginal cerclage than those without cerclage

AutoShot: A Short Video Dataset and State-of-the-Art Shot Boundary Detection

The short-form videos have explosive popularity and have dominated the new social media trends. Prevailing short-video platforms,~\textit{e.g.}, Kuaishou (Kwai), TikTok, Instagram Reels, and YouTube Shorts, have changed the way we consume and create content. For video content creation and understanding, the shot boundary detection (SBD) is one of the most essential components in various scenarios. In this work, we release a new public Short video sHot bOundary deTection dataset, named SHOT, consisting of 853 complete short videos and 11,606 shot annotations, with 2,716 high quality shot boundary annotations in 200 test videos. Leveraging this new data wealth, we propose to optimize the model design for video SBD, by conducting neural architecture search in a search space encapsulating various advanced 3D ConvNets and Transformers. Our proposed approach, named AutoShot, achieves higher F1 scores than previous state-of-the-art approaches, e.g., outperforming TransNetV2 by 4.2%, when being derived and evaluated on our newly constructed SHOT dataset. Moreover, to validate the generalizability of the AutoShot architecture, we directly evaluate it on another three public datasets: ClipShots, BBC and RAI, and the F1 scores of AutoShot outperform previous state-of-the-art approaches by 1.1%, 0.9% and 1.2%, respectively. The SHOT dataset and code can be found in https://github.com/wentaozhu/AutoShot.git .Comment: 10 pages, 5 figures, 3 tables, in CVPR 2023; Top-1 solution for scene / shot boundary detection https://paperswithcode.com/paper/autoshot-a-short-video-dataset-and-state-o

Magnon-mediated interlayer coupling in an all-antiferromagnetic junction

The interlayer coupling mediated by fermions in ferromagnets brings about parallel and anti-parallel magnetization orientations of two magnetic layers, resulting in the giant magnetoresistance, which forms the foundation in spintronics and accelerates the development of information technology. However, the interlayer coupling mediated by another kind of quasi-particle, boson, is still lacking. Here we demonstrate such a static interlayer coupling at room temperature in an antiferromagnetic junction Fe2O3/Cr2O3/Fe2O3, where the two antiferromagnetic Fe2O3 layers are functional materials and the antiferromagnetic Cr2O3 layer serves as a spacer. The N\'eel vectors in the top and bottom Fe2O3 are strongly orthogonally coupled, which is bridged by a typical bosonic excitation (magnon) in the Cr2O3 spacer. Such an orthogonally coupling exceeds the category of traditional collinear interlayer coupling via fermions in ground state, reflecting the fluctuating nature of the magnons, as supported by our magnon quantum well model. Besides the fundamental significance on the quasi-particle-mediated interaction, the strong coupling in an antiferromagnetic magnon junction makes it a realistic candidate for practical antiferromagnetic spintronics and magnonics with ultrahigh-density integration.Comment: 19 pages, 4 figure