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Long Sun,&ast; Jing Wang,&ast; Pan Wei, Wen-Qing Ruan, Jun Guo, Zhi-Yu Yin, Xing Li, Jian-Gang Song Department of Anesthesiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Jian-Gang Song; Xing Li, Department of Anesthesiology, Shuguang Hospital affiliated to Shanghai University of Traditional Chinese Medicine, No. 528 of Zhangheng Road, Pudong District, Shanghai, 201203, People’s Republic of China, Tel +86 13761172886 ; +86 13585562895, Email songjiangang_sjg@126.com; lixinglx06@126.comBackground: Utilizing high-flow nasal cannula (HFNC) oxygen therapy may prevent the collapse of alveoli and improve overall alveolar ventilation. In this study, we aimed to investigate the impact of HFNC on postoperative atelectasis in individuals undergoing robotic-assisted laparoscopic surgery.Methods: Patients undergoing robotic-assisted laparoscopic surgery for rectal cancer were randomly assigned to the control or HFNC groups. After the surgical procedure was complete and the trachea was extubated, both groups underwent an initial lung ultrasound (LUS) scan. In the post-anesthesia care unit (PACU), the control group received conventional nasal cannula oxygen therapy, while the HFNC group received high-flow nasal cannula oxygen therapy. A second LUS scan was conducted before the patient was transferred to the ward. The primary outcome measured was the total LUS score at the time of PACU discharge.Results: In the HFNC group (n = 39), the LUS score and the incidence of atelectasis at PACU discharge were significantly lower compared to the control group (n = 39) [(5 vs 10, P < 0.001), (48.72% vs 82.05%, P = 0.002)]. None of the patients in the HFNC group experienced hypoxemia in the PACU, whereas six patients in the control group did (P = 0.03). Additionally, the minimum SpO2 value in the PACU was notably higher i

This paper provides a comprehensive review of the NTIRE 2024 challenge, focusing on efficient single-image super-resolution (ESR) solutions and their outcomes. The task of this challenge is to super-resolve an input image with a magnification factor of x4 based on pairs of low and corresponding high-resolution images. The primary objective is to develop networks that optimize various aspects such as runtime, parameters, and FLOPs, while still maintaining a peak signal-to-noise ratio (PSNR) of approximately 26.90 dB on the DIV2K_LSDIR_valid dataset and 26.99 dB on the DIV2K_LSDIR_test dataset. In addition, this challenge has 4 tracks including the main track (overall performance), sub-track 1 (runtime), sub-track 2 (FLOPs), and sub-track 3 (parameters). In the main track, all three metrics (ie runtime, FLOPs, and parameter count) were considered. The ranking of the main track is calculated based on a weighted sum-up of the scores of all other sub-tracks. In sub-track 1, the practical runtime performance of the submissions was evaluated, and the corresponding score was used to determine the ranking. In sub-track 2, the number of FLOPs was considered. The score calculated based on the corresponding FLOPs was used to determine the ranking. In sub-track 3, the number of parameters was considered. The score calculated based on the corresponding parameters was used to determine the ranking. RLFN is set as the baseline for efficiency measurement. The challenge had 262 registered participants, and 34 teams made valid submissions. They gauge the state-of-the-art in efficient single-image super-resolution. To facilitate the reproducibility of the challenge and enable other researchers to build upon these findings, the code and the pre-trained model of validated solutions are made publicly available at https://github.com/Amazingren/NTIRE2024_ESR/., Comment: The report paper of NTIRE2024 Efficient Super-resolution, accepted by CVPRW2024

This paper introduces a novel benchmark as part of the AIS 2024 Real-Time Image Super-Resolution (RTSR) Challenge, which aims to upscale compressed images from 540p to 4K resolution (4x factor) in real-time on commercial GPUs. For this, we use a diverse test set containing a variety of 4K images ranging from digital art to gaming and photography. The images are compressed using the modern AVIF codec, instead of JPEG. All the proposed methods improve PSNR fidelity over Lanczos interpolation, and process images under 10ms. Out of the 160 participants, 25 teams submitted their code and models. The solutions present novel designs tailored for memory-efficiency and runtime on edge devices. This survey describes the best solutions for real-time SR of compressed high-resolution images., Comment: CVPR 2024, AI for Streaming (AIS) Workshop

This paper reviews the NTIRE 2024 low light image enhancement challenge, highlighting the proposed solutions and results. The aim of this challenge is to discover an effective network design or solution capable of generating brighter, clearer, and visually appealing results when dealing with a variety of conditions, including ultra-high resolution (4K and beyond), non-uniform illumination, backlighting, extreme darkness, and night scenes. A notable total of 428 participants registered for the challenge, with 22 teams ultimately making valid submissions. This paper meticulously evaluates the state-of-the-art advancements in enhancing low-light images, reflecting the significant progress and creativity in this field., Comment: NTIRE 2024 Challenge Report

Qixiu Li,1,2 Wenhua Jing,3 Zhen Wei,1,2 Yifan Wang,1,2 Long Sun1,2 1Centre for Health Management and Policy Research, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, People’s Republic of China; 2National Health Commission of China (NHC) Key Laboratory of Health Economics and Policy Research (Shandong University), Jinan, Shandong, People’s Republic of China; 3Hospital Service Department, Qilu Hospital of Shandong University, Jinan, Shandong, People’s Republic of ChinaCorrespondence: Long Sun, Centre for Health Management and Policy Research, School of Public Health, Cheeloo College of Medicine, Shandong University, 44 Wenhuaxi Road, Jinan, Shandong, 250012, People’s Republic of China, Email sunlong@sdu.edu.cnBackground: Workplace violence (WPV) had always been the focus of attention in all walks of lives, especially in the health fields. Previous studies had shown it adversely affected mental health for healthcare workers. In addition, both sleep quality and physical activity were supported to have impact on mental health. However, the mechanism of sleep quality and physical activity influence the association between WPV and mental health had not been explored, so the purpose of this paper was to explore this mechanistic link among workplace violence, sleep quality, physical activity, and mental health in Chinese health technicians.Methods: Cross-sectional study was conducted in 3 cities of China, totally 3426 valid questionnaires were collected. WPV, physical activity, and social-demographic variables were evaluated. The Pittsburgh Sleep Quality Index and the Kessler Psychological Distress Scale were used to measure sleep quality and mental health. Descriptive analysis, univariate analysis, Pearson correlation, and moderated mediation analysis were used to estimate prevalence of WPV, association between WPV and mental health, and the role of sleep quality and physical activity on association between WPV and mental

Jie Wang,1,2 Zhen Wei,1,2 Nan Yao,1,2 Caifeng Li,1,2 Long Sun1,2 1Centre for Health Management and Policy Research, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, People’s Republic of China; 2NHC Key Laboratory of Health Economics and Policy Research, Shandong University, Jinan, People’s Republic of ChinaCorrespondence: Long Sun, Centre for Health Management and Policy Research, School of Public Health, Cheeloo College of Medicine, Shandong University, 44 Wenhuaxi Road, Jinan, Shandong, 250012, People’s Republic of China, Tel +86 531-88382678, Email sunlong@sdu.edu.cnPurpose: In recent years, mental health problems have become the most serious social problems worldwide. Past studies have proposed that some links exist between sunlight and mental health; however, relevant studies examining low-dose sunlight exposure populations are lacking. We conducted a study among a group of operating room nurses (ORNs) who work long hours in operating rooms and have limited sunlight exposure. We aim to add to and refine previous researches on the association between mental health and sunlight exposure in community population.Patients and Methods: A total of 787 ORNs were interviewed and analyzed. Mental health, sunlight exposure duration, sociodemographic and work-related variables, and chronic diseases were evaluated. The Kessler 10 scale (K10) was used to assess participants’ mental health status, and their sunlight exposure duration was assessed using their self-reports. Multiple linear regression analysis was adopted to examine the association between sunlight exposure and mental health.Results: The average K10 score of ORNs was 25.41. ORNs exhibit poorer mental health than other populations. Poor mental health was negatively associated with greater sunlight exposure hours per day (β=− 0.378) and sleep regularity (β=− 3.341). Poor mental health was positively associated with chronic disease (β=3.514).Conclusion: This study ind

Although numerous solutions have been proposed for image super-resolution, they are usually incompatible with low-power devices with many computational and memory constraints. In this paper, we address this problem by proposing a simple yet effective deep network to solve image super-resolution efficiently. In detail, we develop a spatially-adaptive feature modulation (SAFM) mechanism upon a vision transformer (ViT)-like block. Within it, we first apply the SAFM block over input features to dynamically select representative feature representations. As the SAFM block processes the input features from a long-range perspective, we further introduce a convolutional channel mixer (CCM) to simultaneously extract local contextual information and perform channel mixing. Extensive experimental results show that the proposed method is $3\times$ smaller than state-of-the-art efficient SR methods, e.g., IMDN, in terms of the network parameters and requires less computational cost while achieving comparable performance. The code is available at https://github.com/sunny2109/SAFMN., Comment: The code is available at https://github.com/sunny2109/SAFMN

Impeller hub corner separation flow (IHCS) has a significant influence on energy conversion of the bulb tubular pump, and its unsteady characteristics are investigated with CFD-based method. The generation mechanism and power loss characteristics of IHCS are investigated by the entropy production method and pressure fluctuation analysis. The main cause can be attributed to the large transverse pressure gradient near the hub at the trailing edge of the impeller, which is aggravated by the circumferential movement trend and the diffuser reverse flow, while the IHCS is significantly weakened with increased flow rate. The undesirable flow behavior is more likely to cause a significant increase in energy loss near the hub region compared to that in the rim region. The relative vortex stretching induced by the velocity gradient is the main cause of the horn-like vortex (HLV), and its intensity and resulting energy loss tend to decrease along the vortex trajectory. The HLV changes the dominant frequency of the pressure fluctuations in the nearby flow field, the value of which increases from 1f r (the blade passing frequency) to 2f r with increased amplitude, mainly due to the lower pressure regions on the impeller suction surface (SS) and HLV vortex core. Due to the effect of rotor-stator interaction (RSI), the HLVs generated between two adjacent impeller blades are cut into several sections by the diffuser vanes and propagate and dissipate along the mainstream direction.

Burst super-resolution has received increased attention in recent years due to its applications in mobile photography. By merging information from multiple shifted images of a scene, burst super-resolution aims to recover details which otherwise cannot be obtained using a simple input image. This paper reviews the NTIRE 2022 challenge on burst super-resolution. In the challenge, the participants were tasked with generating a clean RGB image with 4x higher resolution, given a RAW noisy burst as input. That is, the methods need to perform joint denoising, demosaicking, and super-resolution. The challenge consisted of 2 tracks. Track 1 employed synthetic data, where pixel-accurate high-resolution ground truths are available. Track 2 on the other hand used real-world bursts captured from a handheld camera, along with approximately aligned reference images captured using a DSLR. 14 teams participated in the final testing phase. The top performing methods establish a new state-of-the-art on the burst super-resolution task., Funding Agencies|Huawei; Reality Labs; Bending Spoons; MediaTek; OPPO; Oddity; Voyage81; ETH Zurich (Computer Vision Lab); University of Wurzburg (CAIDAS)

Image super-resolution is a common task on mobile and IoT devices, where one often needs to upscale and enhance low-resolution images and video frames. While numerous solutions have been proposed for this problem in the past, they are usually not compatible with low-power mobile NPUs having many computational and memory constraints. In this Mobile AI challenge, we address this problem and propose the participants to design an efficient quantized image super-resolution solution that can demonstrate a real-time performance on mobile NPUs. The participants were provided with the DIV2K dataset and trained INT8 models to do a high-quality 3X image upscaling. The runtime of all models was evaluated on the Synaptics VS680 Smart Home board with a dedicated edge NPU capable of accelerating quantized neural networks. All proposed solutions are fully compatible with the above NPU, demonstrating an up to 60 FPS rate when reconstructing Full HD resolution images. A detailed description of all models developed in the challenge is provided in this paper., Comment: arXiv admin note: text overlap with arXiv:2105.07825, arXiv:2105.08826, arXiv:2211.04470, arXiv:2211.03885, arXiv:2211.05256

This paper reviews the NTIRE 2022 challenge on efficient single image super-resolution with focus on the proposed solutions and results. The task of the challenge was to super-resolve an input image with a magnification factor of $\times$4 based on pairs of low and corresponding high resolution images. The aim was to design a network for single image super-resolution that achieved improvement of efficiency measured according to several metrics including runtime, parameters, FLOPs, activations, and memory consumption while at least maintaining the PSNR of 29.00dB on DIV2K validation set. IMDN is set as the baseline for efficiency measurement. The challenge had 3 tracks including the main track (runtime), sub-track one (model complexity), and sub-track two (overall performance). In the main track, the practical runtime performance of the submissions was evaluated. The rank of the teams were determined directly by the absolute value of the average runtime on the validation set and test set. In sub-track one, the number of parameters and FLOPs were considered. And the individual rankings of the two metrics were summed up to determine a final ranking in this track. In sub-track two, all of the five metrics mentioned in the description of the challenge including runtime, parameter count, FLOPs, activations, and memory consumption were considered. Similar to sub-track one, the rankings of five metrics were summed up to determine a final ranking. The challenge had 303 registered participants, and 43 teams made valid submissions. They gauge the state-of-the-art in efficient single image super-resolution., Comment: Validation code of the baseline model is available at https://github.com/ofsoundof/IMDN. Validation of all submitted models is available at https://github.com/ofsoundof/NTIRE2022_ESR

Lightweight and efficiency are critical drivers for the practical application of image super-resolution (SR) algorithms. We propose a simple and effective approach, ShuffleMixer, for lightweight image super-resolution that explores large convolution and channel split-shuffle operation. In contrast to previous SR models that simply stack multiple small kernel convolutions or complex operators to learn representations, we explore a large kernel ConvNet for mobile-friendly SR design. Specifically, we develop a large depth-wise convolution and two projection layers based on channel splitting and shuffling as the basic component to mix features efficiently. Since the contexts of natural images are strongly locally correlated, using large depth-wise convolutions only is insufficient to reconstruct fine details. To overcome this problem while maintaining the efficiency of the proposed module, we introduce Fused-MBConvs into the proposed network to model the local connectivity of different features. Experimental results demonstrate that the proposed ShuffleMixer is about 6x smaller than the state-of-the-art methods in terms of model parameters and FLOPs while achieving competitive performance. In NTIRE 2022, our primary method won the model complexity track of the Efficient Super-Resolution Challenge [23]. The code is available at https://github.com/sunny2109/MobileSR-NTIRE2022., Comment: Winner of the model complexity track in NTIRE2022 Efficient Super-Resolution Challenge, CVPR 2022. The code is available at https://github.com/sunny2109/MobileSR-NTIRE2022

Long Sun,1,2 Keqing Li,3 Lili Zhang,3 Yunshu Zhang3 1Centre for Health Management and Policy Research, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, People’s Republic of China; 2National Health Commission of China Key Laboratory for Health Economics and Policy Research (Shandong University), Jinan, Shandong, People’s Republic of China; 3Department of Sleep Medicine, Hebei Provincial Mental Health Center, Baoding, Hebei, People’s Republic of ChinaCorrespondence: Yunshu Zhang, Department of Sleep Medicine, Hebei Provincial Mental Health Center, 572 Dongfengdong Road, Baoding, Hebei, 071000, People’s Republic of China, Tel +86 312-507-9277, Email yunshucoffee@sina.comObjective: Cognitive impairment is a rapidly growing global public health problem in China and worldwide. In the recent decades, emerging studies have explored the associations between sleep disturbances and cognitive impairment. However, the variety of the results imply us that further studies should be conducted for the associations.Methods: This is a cross-sectional study conducted between August and October 2018 in five cities in Hebei province, China. Subjects were 21,376 community residents. Cognitive impairment was screened by the Chinese version of the Mini-Mental State Examination (MMSE). Scales of Athens Insomnia Scale (AIS), Berlin Questionnaire (BQ), REM (rapid eye movement) Sleep Behavior Disorder Questionnaire (RBDQ-HK), Ullanlinna Narcolepsy Scale (CUNS), and Cambridge-Hopkins Restless Legs Syndrome Questionnaire (CH-RLSq) were used to access insomnia, sleep apnea, REM sleep behavior disorder, narcolepsy, and restless leg syndrome.Results: The mean ± SD (standard error) of MMSE, AIS, RBDQ-HK, and CUNS were 27.95 ± 4.79, 2.16 ± 3.39, 5.55 ± 7.75, and 3.76 ± 2.31, respectively. Among the participants, 10.6% and 1.5% of the participants were identified as having a high risk of sleep apnea and restless leg syndrome, respectively. The res

Long Sun,1,* Juan Xu,2,* Weizhong Wang,3 Fang He3 1Department of Clinical Laboratory, Hangzhou Women’s Hospital, Hangzhou Maternity and Child Health Care Hospital, Hangzhou, Zhejiang 310008, People’s Republic of China; 2Institute of Hygiene, Zhejiang Academy of Medical Sciences, Hangzhou Medical College, Hangzhou, Zhejiang 310013, People’s Republic of China; 3Department of Clinical Laboratory, Zhejiang Provincial People’s Hospital, People’s Hospital of Hangzhou Medical College, Hangzhou, Zhejiang 310014, People’s Republic of China*These authors contributed equally to this workCorrespondence: Fang He Tel/Fax +86-571-8821-5596Email hetrue@163.comPurpose: The emergence of vancomycin-resistant enterococci (VRE) dramatically narrows therapeutic options. Although the prevalence of VRE in China has maintained a low level, VRE outbreaks have been reported in some tertiary hospitals in the developed areas of China. The clonal background of vanA-positive Enterococcus faecium strains has not been well characterized in China. Here, we report the whole-genome sequence of a vanA-type vancomycin-resistant E. faecium belonging to sequence type (ST) 78 isolated from a urinary tract infection in China.Patients and Methods: A vancomycin-resistant E. faecium was isolated from a 66-year-old male patient diagnosed with brainstem hemorrhage. Antibiotic susceptibility assays were performed according to the guidelines of the Clinical and Laboratory Standards Institute (CLSI). Complete genome sequencing was performed using both the HiSeqTM 4000 platform and the MinION platform. Plasmid, genomic and phylogenetic relationship analysis were further performed.Results: E. faecium VRE1 was resistant to all antimicrobials tested except for tetracyclines and oxazolidinones. The whole genome of E. faecium VRE1 was composed of one chromosomal DNA and four plasmids. Two virulence genes and five antimicrobial resistance genes were identified. I

This paper reviews the AIM 2020 challenge on efficient single image super-resolution with focus on the proposed solutions and results. The challenge task was to super-resolve an input image with a magnification factor x4 based on a set of prior examples of low and corresponding high resolution images. The goal is to devise a network that reduces one or several aspects such as runtime, parameter count, FLOPs, activations, and memory consumption while at least maintaining PSNR of MSRResNet. The track had 150 registered participants, and 25 teams submitted the final results. They gauge the state-of-the-art in efficient single image super-resolution.

This paper reviews the AIM 2019 challenge on constrained example-based single image super-resolution with focus on proposed solutions and results. The challenge had 3 tracks. Taking the three main aspects (i.e., number of parameters, inference/running time, fidelity (PSNR)) of MSRResNet as the baseline, Track 1 aims to reduce the amount of parameters while being constrained to maintain or improve the running time and the PSNR result, Tracks 2 and 3 aim to optimize running time and PSNR result with constrain of the other two aspects, respectively. Each track had an average of 64 registered participants, and 12 teams submitted the final results. They gauge the state-of-the-art in single image super-resolution.

Jing-Xun Wu,1,* Qi He,1,* Feng Ye,1,* Qing-Xia Zhou,2 Hao-Jun Chen,3 Long Sun,3 Hua Wu3 1Department of Medical Oncology, Xiamen Cancer Hospital, The First Affiliated Hospital of Xiamen University, Xiamen, China; 2Department of Medical Oncology, Wuzhong People’s Hospital, Wuzhong, China; 3Department of Nuclear Medicine and Minnan PET Center, Xiamen Cancer Hospital, The First Affiliated Hospital of Xiamen University, Xiamen, China *These authors contributed equally to this work Purpose: The great efficacy of EGFR tyrosine kinase inhibitors (EGFR-TKIs) has been identified in patients with advanced non-small-cell lung cancer (NSCLC) who harbor EGFR mutations. However, it has not yet been established in postoperative adjuvant therapy. Patients and methods: To compare the prognosis and toxicity of EGFR-TKI-based adjuvant therapy and non-EGFR-TKI-based adjuvant therapy in resected NSCLC with sensitive EGFR mutations, we performed this meta-analysis of all eligible randomized controlled trials (RCTs). Results: A comprehensive literature search of electronic databases (from inception to December 31, 2017) was performed. Additionally, abstracts presented at the American Society of Clinical Oncology conferences and World Conference on Lung Cancer held between January 2000 and November 2017 were searched to identify relevant trials. Disease-free survival (DFS), overall survival (OS), and grade 3 or 4 toxicities were analyzed. Five RCTs were selected, and 560 participants were included. This meta-analysis demonstrated that EGFR-TKI-based adjuvant therapy was associated with better DFS compared with non-EGFR-TKI-based therapy (HR =0.52, 95% CI 0.34–0.78, P=0.002). Pooled estimate has showed the trend of superiority of EGFR-TKI-based therapy in the aspect of OS (HR =0.65, 95% CI 0.22–1.91, P=0.43); however, the difference was not significant. The incidence rate of grade 3–4 toxicities of EGFR-TKI-based regimens was significantly higher for r

A three-dimensional immersed boundary method was implemented into a Large Eddy Simulation (LES) with advanced subgrid-scale modeling capability. In this way, obstacles in the urban atmospheric boundary layer such as buildings and hills could be represented without changing the Cartesian grid. These numerical methods are applied in two urban environment investigations. The first explores the effect of hilly urban morphology on dispersion characteristics in the urban boundary layer. The second investigate the application of wall functions for building convection heat transfer in large eddy simulation. Air flow and dispersion in urban areas are strongly affected by the presence of buildings. In natural settings hills strongly impact dispersion. Five simulations of flow over building arrays over flat terrain and witch of Agnesi hills with maximum slope of 0.26 were conducted to study turbulence and dispersion properties in and above the canopy. While the small hill reduces the shear stress and velocity variance above the urban canopy compared to the flat urban array, the shear stress increases for larger hills. The TKE in the canopy downwind of the hill decreased below the value for the flat urban case, but canopy ventilation for the hilly cases was several times larger than for the flat case, especially near the hill crest. Therefore, urban dispersion models should account for these relatively moderate terrain changes to produce accurate results. In urban energy balance models, convection heat transfer model is often over-simplified by using a uniform convection heat transfer coefficient (CHTC) for each building surface. We consider more complex flow patterns by implementing a wall function to calculate the local CHTC from local velocities provided by LES. Simulations consisting of single building, 3 x 3 building arrays and 6 x 6 building arrays with neutral and unstable conditions were performed. Validation showed similar results as a low Reynolds number simulation re

Persistent memory provides high-performance data persistence at main memory. Memory writes need to be performed in strict order to satisfy storage consistency requirements and enable correct recovery from system crashes. Unfortunately, adhering to such a strict order significantly degrades system performance and persistent memory endurance. This paper introduces a new mechanism, Loose-Ordering Consistency (LOC), that satisfies the ordering requirements at significantly lower performance and endurance loss. LOC consists of two key techniques. First, Eager Commit eliminates the need to perform a persistent commit record write within a transaction. We do so by ensuring that we can determine the status of all committed transactions during recovery by storing necessary metadata information statically with blocks of data written to memory. Second, Speculative Persistence relaxes the write ordering between transactions by allowing writes to be speculatively written to persistent memory. A speculative write is made visible to software only after its associated transaction commits. To enable this, our mechanism supports the tracking of committed transaction ID and multi-versioning in the CPU cache. Our evaluations show that LOC reduces the average performance overhead of memory persistence from 66.9% to 34.9% and the memory write traffic overhead from 17.1% to 3.4% on a variety of workloads., Comment: This paper has been accepted by IEEE Transactions on Parallel and Distributed Systems