Learning Correction Errors via Frequency-Self Attention for Blind Image Super-Resolution

Previous approaches for blind image super-resolution (SR) have relied on degradation estimation to restore high-resolution (HR) images from their low-resolution (LR) counterparts. However, accurate degradation estimation poses significant challenges. The SR model's incompatibility with degradation estimation methods, particularly the Correction Filter, may significantly impair performance as a result of correction errors. In this paper, we introduce a novel blind SR approach that focuses on Learning Correction Errors (LCE). Our method employs a lightweight Corrector to obtain a corrected low-resolution (CLR) image. Subsequently, within an SR network, we jointly optimize SR performance by utilizing both the original LR image and the frequency learning of the CLR image. Additionally, we propose a new Frequency-Self Attention block (FSAB) that enhances the global information utilization ability of Transformer. This block integrates both self-attention and frequency spatial attention mechanisms. Extensive ablation and comparison experiments conducted across various settings demonstrate the superiority of our method in terms of visual quality and accuracy. Our approach effectively addresses the challenges associated with degradation estimation and correction errors, paving the way for more accurate blind image SR.Comment: 16 page

IC-FPS: Instance-Centroid Faster Point Sampling Module for 3D Point-base Object Detection

3D object detection is one of the most important tasks in autonomous driving and robotics. Our research focuses on tackling low efficiency issue of point-based methods on large-scale point clouds. Existing point-based methods adopt farthest point sampling (FPS) strategy for downsampling, which is computationally expensive in terms of inference time and memory consumption when the number of point cloud increases. In order to improve efficiency, we propose a novel Instance-Centroid Faster Point Sampling Module (IC-FPS) , which effectively replaces the first Set Abstraction (SA) layer that is extremely tedious. IC-FPS module is comprised of two methods, local feature diffusion based background point filter (LFDBF) and Centroid-Instance Sampling Strategy (CISS). LFDBF is constructed to exclude most invalid background points, while CISS substitutes FPS strategy by fast sampling centroids and instance points. IC-FPS module can be inserted to almost every point-based models. Extensive experiments on multiple public benchmarks have demonstrated the superiority of IC-FPS. On Waymo dataset, the proposed module significantly improves performance of baseline model and accelerates inference speed by 3.8 times. For the first time, real-time detection of point-based models in large-scale point cloud scenario is realized

EA-BEV: Edge-aware Bird' s-Eye-View Projector for 3D Object Detection

In recent years, great progress has been made in the Lift-Splat-Shot-based (LSS-based) 3D object detection method, which converts features of 2D camera view and 3D lidar view to Bird's-Eye-View (BEV) for feature fusion. However, inaccurate depth estimation (e.g. the 'depth jump' problem) is an obstacle to develop LSS-based methods. To alleviate the 'depth jump' problem, we proposed Edge-Aware Bird's-Eye-View (EA-BEV) projector. By coupling proposed edge-aware depth fusion module and depth estimate module, the proposed EA-BEV projector solves the problem and enforces refined supervision on depth. Besides, we propose sparse depth supervision and gradient edge depth supervision, for constraining learning on global depth and local marginal depth information. Our EA-BEV projector is a plug-and-play module for any LSS-based 3D object detection models, and effectively improves the baseline performance. We demonstrate the effectiveness on the nuScenes benchmark. On the nuScenes 3D object detection validation dataset, our proposed EA-BEV projector can boost several state-of-the-art LLS-based baselines on nuScenes 3D object detection benchmark and nuScenes BEV map segmentation benchmark with negligible increment of inference time

Fabrication Process Independent And Robust Aggregation Of Detonation Nanodiamonds In Aqueous Media

In the past detonation nanodiamonds (DNDs), sized 3–5 nm, have been praised for their colloidal stability in aqueous media, thereby attracting vast interest in a wide range of applications including nanomedicine. More recent studies have challenged the consensus that DNDs are monodispersed after their fabrication process, with their aggregate formation dynamics poorly understood. Here we reveal that DNDs in aqueous solution, regardless of their post-synthesis de-agglomeration and purification methods, exhibit hierarchical aggregation structures consisting of chain-like and cluster aggregate morphologies. With a novel characterization approach combining machine learning with direct cryo-transmission electron microscopy and with X-ray scattering and vibrational spectroscopy, we show that their aggregate morphologies of chain and cluster ratios and the corresponding size and fractal dimension distributions vary with the post-synthesis treatment methods. In particular DNDs with positive ζ-potential form to a hierarchical structure that assembles aggregates into large networks. DNDs purified with the gas phase annealing and oxidation tend to have more chain-like aggregates. Our findings provide important contribution in understanding the DND interparticle interactions to control the size, polydispersity and aggregation of DNDs for their desired applications

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

Winning the Blue Sky Defense War: Assessing Air Pollution Prevention and Control Action Based on Synthetic Control Method

Undoubtedly, the rapid development of urbanization and industrialization in China has led to environmental problems, among which air pollution is particularly prominent. In response, the Chinese government has introduced a series of policies, including the Air Pollution Control and Prevention Action Plan (APPA), which is one of the most stringent environmental regulations in history. The scientific evaluation of the implementation of this regulation is important for China to win the battle of blue sky. Therefore, this study uses a synthetic control method to explore the effects of APPA on air pollution (AP) based on data of 30 provinces from 2000 to 2019. The study concludes that (1) APPA significantly reduces AP in the treatment provinces, and subsequent robustness tests validate our findings. However, the persistence of the policy effect is short in some provinces, and the rate of AP reduction slows down or even rebounds in the later stages of the policy. (2) The reduction effect of APPA varies significantly between regions and provinces. (3) The results of mechanism tests show that APPA reduces AP through high-quality economic development, population agglomeration, control of carbon emissions, and optimization of energy structure. Based on the above findings, targeted recommendations are proposed to promote AP control in China and win the blue sky defense war

Mechatronics System for ME240 Course Objectives

At the University of Michigan, ME240: Introduction to Dynamics and Vibrations is a core class for undergraduate mechanical engineering students. Topics such as particle kinetics, angular motion, and vibrations are introduced in this course and understanding them can be difficult, especially due to a lack of many physical models to demonstrate them. The course concepts are fundamental for later courses and in real-life applications. Researchers have studied the effects of experiential learning on students' learning and have proven that it is extremely beneficial in long-term learning. Experiential learning places an emphasis on experimentation and experience that students can use to help contextualize topics they have learned. Students can become more engaged in the classroom and connect theoretical behaviors and concepts to real-life applications. Professors currently have online simulations and simple models and have requested a model that incorporates sensors and encoders. We are tasked with creating a mechatronic system for use as a teaching aid and learning tool.Jeffrey KollerAlex ShorterUniversity of Michigan Department of Mechanical Engineeringhttp://deepblue.lib.umich.edu/bitstream/2027.42/177467/1/UM_Koller_W23_T16_Mechatronics-System-for.pd

Microstructure and Texture Evolution of Fe-33Mn-3Si-3Al TWIP Steel on Strain

International audienceThe microstructure and texture evolution of Fe-33Mn-3Si-3Al twinning induced plasticity (TWIP) steel were studied by the scanning electron microscope (SEM) and X-ray diffraction (XRD) at room temperature. After quasi-static tensile, the texture evolution of different strain was observed. It was shown that the Goss and Brass components increased within the strain range of less than 0.6. Whereas, the main components were decreased when the strain levels were greater than 0.6. This behavior was attributed to the low stacking fault energy (SFE) and was related to the strain energy of this high manganese steel. At high strain levels, the high strain energy may contribute to the Brass components transition to the A (rot-Brass) components

Treatment and benefit analysis of wastewater from construction of hydropower project

In order to treat oil and other pollutants in downstream surface water causing by the construction process of a hydropower project, many methods were used. Besides that, a set of flocculation and precipitation facilities was designed as an emergency device for entire construction site. Good results were achieved in the treatment of construction wastewater, which has obvious economic and environmental benefits and has reference value for similar projects