Dear Editor,Since the existing hyperspectral image denoising methods suffer from excessive or incomplete denoising,leading to information distortion and loss,this letter proposes a deep denoising network in the freque...Dear Editor,Since the existing hyperspectral image denoising methods suffer from excessive or incomplete denoising,leading to information distortion and loss,this letter proposes a deep denoising network in the frequency domain,termed D2Net.Our motivation stems from the observation that images from different hyperspectral image(HSI)bands share the same structural and contextual features while the reflectance variations in the spectra are mainly fallen on the details and textures.展开更多
Mobile Edge Computing(MEC)is a technology designed for the on-demand provisioning of computing and storage services,strategically positioned close to users.In the MEC environment,frequently accessed content can be dep...Mobile Edge Computing(MEC)is a technology designed for the on-demand provisioning of computing and storage services,strategically positioned close to users.In the MEC environment,frequently accessed content can be deployed and cached on edge servers to optimize the efficiency of content delivery,ultimately enhancing the quality of the user experience.However,due to the typical placement of edge devices and nodes at the network’s periphery,these components may face various potential fault tolerance challenges,including network instability,device failures,and resource constraints.Considering the dynamic nature ofMEC,making high-quality content caching decisions for real-time mobile applications,especially those sensitive to latency,by effectively utilizing mobility information,continues to be a significant challenge.In response to this challenge,this paper introduces FT-MAACC,a mobility-aware caching solution grounded in multi-agent deep reinforcement learning and equipped with fault tolerance mechanisms.This approach comprehensively integrates content adaptivity algorithms to evaluate the priority of highly user-adaptive cached content.Furthermore,it relies on collaborative caching strategies based onmulti-agent deep reinforcement learningmodels and establishes a fault-tolerancemodel to ensure the system’s reliability,availability,and persistence.Empirical results unequivocally demonstrate that FTMAACC outperforms its peer methods in cache hit rates and transmission latency.展开更多
Corona Virus Disease 2019(COVID-19)has brought the new challenges to scientific research.Isodon suzhouensis has good anti-inflammatory and antioxidant stress effects,which is considered as a potential treatment for CO...Corona Virus Disease 2019(COVID-19)has brought the new challenges to scientific research.Isodon suzhouensis has good anti-inflammatory and antioxidant stress effects,which is considered as a potential treatment for COVID-19.The possibility for the treatment of COVID-19 with I.suzhouensis and its potential mechanism of action were explored by employing molecular docking and network pharmacology.Network pharmacology and molecular docking were used to screen drug targets,and lipopolysaccharide(LPS)induced RAW264.7 and NR8383 cells inflammation model was used for experimental verification.Collectively a total of 209 possible linkages against 18 chemical components from I.suzhouensis and 1194 COVID-19 related targets were selected.Among these,164 common targets were obtained from the intersection of I.suzhouensis and COVID-19.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enriched 582 function targets and 87 target proteins pathways,respectively.The results from molecular docking studies revealed that rutin,vitexin,isoquercitrin and quercetin had significant binding ability with 3 chymotrypsin like protease(3CLpro)and angiotensin converting enzyme 2(ACE2).In vitro studies showed that I.suzhouensis extract(ISE)may inhibit the activation of PI3K/Akt pathway and the expression level of downstream proinflammatory factors by inhibiting the activation of epidermal growth factor receptor(EGFR)in RAW264.7 cells induced by LPS.In addition,ISE was able to inhibit the activation of TLR4/NF-κB signaling pathway in NR8383 cells exposed to LPS.Overall,the network pharmacology and in vitro studies conclude that active components from I.suzhouensis have strong therapeutic potential against COVID-19 through multi-target,multi-pathway dimensions and can be a promising candidate against COVID-19.展开更多
Mobile Edge Computing(MEC)is a promising technology that provides on-demand computing and efficient storage services as close to end users as possible.In an MEC environment,servers are deployed closer to mobile termin...Mobile Edge Computing(MEC)is a promising technology that provides on-demand computing and efficient storage services as close to end users as possible.In an MEC environment,servers are deployed closer to mobile terminals to exploit storage infrastructure,improve content delivery efficiency,and enhance user experience.However,due to the limited capacity of edge servers,it remains a significant challenge to meet the changing,time-varying,and customized needs for highly diversified content of users.Recently,techniques for caching content at the edge are becoming popular for addressing the above challenges.It is capable of filling the communication gap between the users and content providers while relieving pressure on remote cloud servers.However,existing static caching strategies are still inefficient in handling the dynamics of the time-varying popularity of content and meeting users’demands for highly diversified entity data.To address this challenge,we introduce a novel method for content caching over MEC,i.e.,PRIME.It synthesizes a content popularity prediction model,which takes users’stay time and their request traces as inputs,and a deep reinforcement learning model for yielding dynamic caching schedules.Experimental results demonstrate that PRIME,when tested upon the MovieLens 1M dataset for user request patterns and the Shanghai Telecom dataset for user mobility,outperforms its peers in terms of cache hit rates,transmission latency,and system cost.展开更多
The possible configurations of pyrrole absorbed on a Si(100)surface have been investigated by x-ray photoelectron spectroscopy(XPS)and near-edge x-ray absorption fine structure(NEXAFS)spectra.The C-1s XPS and NEXAFS s...The possible configurations of pyrrole absorbed on a Si(100)surface have been investigated by x-ray photoelectron spectroscopy(XPS)and near-edge x-ray absorption fine structure(NEXAFS)spectra.The C-1s XPS and NEXAFS spectra of these adsorption configurations have been calculated by using the density functional theory(DFT)method and fullcore hole(FCH)approximation to investigate the relationship between the adsorption configurations and the spectra.The result shows that the XPS and NEXAFS spectra are structurally dependent on the configurations of pyrrole absorbed on the Si(100)surface.Compared with the XPS,the NEXAFS spectra are relatively sensitive to the adsorption configurations and can accurately identify them.The NEXAFS decomposition spectra produced by non-equivalent carbon atoms have also been calculated and show that the spectral features vary with the diverse types of carbon atoms and their structural environments.展开更多
The rotary motion deblurring is an inevitable procedure when the imaging seeker is mounted in the rotating missiles.Traditional rotary motion deblurring methods suffer from ringing artifacts and noise,especially for l...The rotary motion deblurring is an inevitable procedure when the imaging seeker is mounted in the rotating missiles.Traditional rotary motion deblurring methods suffer from ringing artifacts and noise,especially for large blur extents.To solve the above problems,we propose a progressive rotary motion deblurring framework consisting of a coarse deblurring stage and a refinement stage.In the first stage,we design an adaptive blur extents factor(BE factor)to balance noise suppression and details reconstruction.And a novel deconvolution model is proposed based on BE factor.In the second stage,a triplescale deformable module CNN(TDM-CNN)is designed to reduce the ringing artifacts,which can exploit the 2D information of an image and adaptively adjust spatial sampling locations.To establish a standard evaluation benchmark,a real-world rotary motion blur dataset is proposed and released,which includes rotary blurred images and corresponding ground truth images with different blur angles.Experimental results demonstrate that the proposed method outperforms the state-of-the-art models on synthetic and real-world rotary motion blur datasets.The code and dataset are available at https://github.com/JinhuiQin/RotaryDeblurring.展开更多
Long-term urban traffic flow prediction is an important task in the field of intelligent transportation,as it can help optimize traffic management and improve travel efficiency.To improve prediction accuracy,a crucial...Long-term urban traffic flow prediction is an important task in the field of intelligent transportation,as it can help optimize traffic management and improve travel efficiency.To improve prediction accuracy,a crucial issue is how to model spatiotemporal dependency in urban traffic data.In recent years,many studies have adopted spatiotemporal neural networks to extract key information from traffic data.However,most models ignore the semantic spatial similarity between long-distance areas when mining spatial dependency.They also ignore the impact of predicted time steps on the next unpredicted time step for making long-term predictions.Moreover,these models lack a comprehensive data embedding process to represent complex spatiotemporal dependency.This paper proposes a multi-scale persistent spatiotemporal transformer(MSPSTT)model to perform accurate long-term traffic flow prediction in cities.MSPSTT adopts an encoder-decoder structure and incorporates temporal,periodic,and spatial features to fully embed urban traffic data to address these issues.The model consists of a spatiotemporal encoder and a spatiotemporal decoder,which rely on temporal,geospatial,and semantic space multi-head attention modules to dynamically extract temporal,geospatial,and semantic characteristics.The spatiotemporal decoder combines the context information provided by the encoder,integrates the predicted time step information,and is iteratively updated to learn the correlation between different time steps in the broader time range to improve the model’s accuracy for long-term prediction.Experiments on four public transportation datasets demonstrate that MSPSTT outperforms the existing models by up to 9.5%on three common metrics.展开更多
Dear Editor,We report a case with trans-photorefractive keratectomy(PRK)for recurrent epithelial corneal erosion caused by cooking oil after EVO-implantable contact lens(ICL)(EVO Visian ICL;STAAR Surgical AG,Switzerla...Dear Editor,We report a case with trans-photorefractive keratectomy(PRK)for recurrent epithelial corneal erosion caused by cooking oil after EVO-implantable contact lens(ICL)(EVO Visian ICL;STAAR Surgical AG,Switzerland),which should be distinguished from postoperative complications of EVO-ICL.Most corneal burns are classified as chemical and thermal burns,referring to direct contact injury to the cornea.展开更多
This study proposes a novel general image fusion framework based on cross-domain long-range learning and Swin Transformer,termed as SwinFusion.On the one hand,an attention-guided cross-domain module is devised to achi...This study proposes a novel general image fusion framework based on cross-domain long-range learning and Swin Transformer,termed as SwinFusion.On the one hand,an attention-guided cross-domain module is devised to achieve sufficient integration of complementary information and global interaction.More specifically,the proposed method involves an intra-domain fusion unit based on self-attention and an interdomain fusion unit based on cross-attention,which mine and integrate long dependencies within the same domain and across domains.Through long-range dependency modeling,the network is able to fully implement domain-specific information extraction and cross-domain complementary information integration as well as maintaining the appropriate apparent intensity from a global perspective.In particular,we introduce the shifted windows mechanism into the self-attention and cross-attention,which allows our model to receive images with arbitrary sizes.On the other hand,the multi-scene image fusion problems are generalized to a unified framework with structure maintenance,detail preservation,and proper intensity control.Moreover,an elaborate loss function,consisting of SSIM loss,texture loss,and intensity loss,drives the network to preserve abundant texture details and structural information,as well as presenting optimal apparent intensity.Extensive experiments on both multi-modal image fusion and digital photography image fusion demonstrate the superiority of our SwinFusion compared to the state-of-theart unified image fusion algorithms and task-specific alternatives.Implementation code and pre-trained weights can be accessed at https://github.com/Linfeng-Tang/SwinFusion.展开更多
Image fusion aims to integrate complementary information in source images to synthesize a fused image comprehensively characterizing the imaging scene. However, existing image fusion algorithms are only applicable to ...Image fusion aims to integrate complementary information in source images to synthesize a fused image comprehensively characterizing the imaging scene. However, existing image fusion algorithms are only applicable to strictly aligned source images and cause severe artifacts in the fusion results when input images have slight shifts or deformations. In addition,the fusion results typically only have good visual effect, but neglect the semantic requirements of high-level vision tasks.This study incorporates image registration, image fusion, and semantic requirements of high-level vision tasks into a single framework and proposes a novel image registration and fusion method, named Super Fusion. Specifically, we design a registration network to estimate bidirectional deformation fields to rectify geometric distortions of input images under the supervision of both photometric and end-point constraints. The registration and fusion are combined in a symmetric scheme, in which while mutual promotion can be achieved by optimizing the naive fusion loss, it is further enhanced by the mono-modal consistent constraint on symmetric fusion outputs. In addition, the image fusion network is equipped with the global spatial attention mechanism to achieve adaptive feature integration. Moreover, the semantic constraint based on the pre-trained segmentation model and Lovasz-Softmax loss is deployed to guide the fusion network to focus more on the semantic requirements of high-level vision tasks. Extensive experiments on image registration, image fusion,and semantic segmentation tasks demonstrate the superiority of our Super Fusion compared to the state-of-the-art alternatives.The source code and pre-trained model are publicly available at https://github.com/Linfeng-Tang/Super Fusion.展开更多
BACKGROUND： Trauma can damage the spinal cord or cauda equina to different degrees. Previous studies have verified that traditional Chinese medicine has effects on spinal cord injury via a variety of pathways. OBJECT...BACKGROUND： Trauma can damage the spinal cord or cauda equina to different degrees. Previous studies have verified that traditional Chinese medicine has effects on spinal cord injury via a variety of pathways. OBJECTIVE： To observe changes in hemorheology and inflammatory factors in spinal cord injury rats following treatment with the Chinese medicine Jisuikang, to verify the dose-dependent effect of Jisuikang, and to compare its effects with the effects of prednisone. DESIGN, TIME AND SETTING： A randomized study was performed at the Research Institute of Orthopedics, and Experimental Center of First Clinical Medical College, Nanjing University of Traditional Chinese Medicine, China from September 2007 to March 2008. MATERIALS： Jisuikang powdered extract, composed of milkvetch root （30 g）, Chinese angelica （12 g）, red peony root （12 g）, earthworm （10 g）, szechwan lovage rhizome （10 g）, peach seed （10 g） and safflower （10 g） was provided by the Experimental Center, First Clinical Medical College, Nanjing University of Traditional Chinese medicine. Each gram of powdered extract was equivalent to 6.47 g crude drug. METHODS： A total of 72 Sprague Dawley rats were randomly assigned into 6 groups （n = 12）. Rat models of spinal cord injury were established using the occlusion method. Rats in the model group were treated with distilled water. Rats in the 25 g/kg, 12.5 g/kg, and 6.25 g/kg Jisuikang groups were given 25 g＆g, 12.5 g/kg, or 6.25 g/kg Jisuikang by gavage, for 14 days. Rats in the prednisone group received 0.06 g/kg prednisone by gavage, for 7 days. Rats in the normal group were given the same volume of distilled water. The volume of administration was 15 mL/kg. MAIN OUTCOME MEASURES： Rat serum interleukin-10, tumor necrosis factor- α （TNF-α ）, nitric oxide, nitric oxide synthase levels, malondialdehyde content, superoxide dismutase activity and whole blood viscosity were measured in each group. Spinal cord around the site of the model was collected. Half the spinal cord was used for histopathologic examination. The other half was used for measurement of nitric oxide and NOS levels, malondialdehyde contents, and superoxide dismutase activity. RESULTS： Superoxide dismutase activity was higher in the 25 g/kg Jisuikang group than in the model group Malondialdehyde contents, nitric oxide and NOS levels were lower in the 25 g/kg and 12.5 g/kg Jisuikang groups compared with the model group. Whole blood viscosity was lower in the 25 g/kg and 12.5 g/kg Jisuikang groups compared with the model group （P 〈 0.05-0.01）. Serum TNF- α content was lower in each Jisuikang group compared with the model group （P 〈 0.05-0.01）. Serum interleukin-10 levels were greater in the prednisone group and each Jisuikang group compared with the model group （P 〈 0.01）. Mild hemorrhage and necrosis in the rat spinal cord, and unclear neural cell swelling were seen in the 25 g/kg Jisuikang group： Severe hemorrhage and necrosis in the rat spinal cord, and distinct neural cell swelling were seen in the 12.5 g/kg Jisuikang group. Edema in the white matter was found in the 6.25 g/kg Jisuikang group. Pathological changes in the prednisone group were identical to the 25 g/kg and 12.5 g/kg Jisuikang groups. CONCLUSION： Jisuikang inhibits nitric oxide synthase expression, reduces nitric oxide and TNF-α levels decreases malondialdehyde content, increases interleukin-10 levels and superoxide dismutase activity, improves indices of hemorheology, and prevents secondary changes in spinal cord injury, resulting in relieving pathological changes in spinal cord tissue. The outcome was significant in the 25 g/kg Jisuikang group compared with the 12.5 g/kg Jisuikang group.展开更多
The technology deployed for lithium-ion battery state of charge(SOC)estimation is an important part of the design of electric vehicle battery management systems.Accurate SOC estimation can forestall excessive charging...The technology deployed for lithium-ion battery state of charge(SOC)estimation is an important part of the design of electric vehicle battery management systems.Accurate SOC estimation can forestall excessive charging and discharging of lithium-ion batteries,thereby improving discharge efficiency and extending cycle life.In this study,the key lithium-ion battery SOC estimation technologies are summarized.First,the research status of lithium-ion battery modeling is introduced.Second,the main technologies and difficulties in model parameter identification for lithium-ion batteries are discussed.Third,the development status and advantages and disadvantages of SOC estimation methods are summarized.Finally,the current research problems and prospects for development trends are summarized.展开更多
Infrared(IR) small target detection is one of the key technologies of infrared search and track(IRST)systems. Existing methods have some limitations in detection performance, especially when the target size is irregul...Infrared(IR) small target detection is one of the key technologies of infrared search and track(IRST)systems. Existing methods have some limitations in detection performance, especially when the target size is irregular or the background is complex. In this paper, we propose a pixel-level local contrast measure(PLLCM), which can subdivide small targets and backgrounds at pixel level simultaneously.With pixel-level segmentation, the difference between the target and the background becomes more obvious, which helps to improve the detection performance. First, we design a multiscale sliding window to quickly extract candidate target pixels. Then, a local window based on random walker(RW) is designed for pixel-level target segmentation. After that, PLLCM incorporating probability weights and scale constraints is proposed to accurately measure local contrast and suppress various types of background interference. Finally, an adaptive threshold operation is applied to separate the target from the PLLCM enhanced map. Experimental results show that the proposed method has a higher detection rate and a lower false alarm rate than the baseline algorithms, while achieving a high speed.展开更多
Dear Editor,3×3 Infrared imaging,generally,of low quality,plays an important role in security surveillance and target detection.In this letter,we improve the quality of infrared images by combining both hardware ...Dear Editor,3×3 Infrared imaging,generally,of low quality,plays an important role in security surveillance and target detection.In this letter,we improve the quality of infrared images by combining both hardware and software.To this end,an infrared light field imaging enhancement system is built for the first time,including a infrared light field imaging device,a large-scale infrared light field dataset(IRLF-WHU),and a progressive fusion network for infrared image enhancement(IR-PFNet).展开更多
Rhodamine molecules are one of the most used dyes for applications related to Raman spectroscopy. We have systematically studied Raman spectra of Rhodamine 6G, Rhodamine 123, and Rhodamine B （RhB） molecules using de...Rhodamine molecules are one of the most used dyes for applications related to Raman spectroscopy. We have systematically studied Raman spectra of Rhodamine 6G, Rhodamine 123, and Rhodamine B （RhB） molecules using density functional theory. It is found that with BP86 functional the calculated Raman spectra of cationic Rhodamine molecules are in good agreement with corresponding experimental spectra in aqueous solution. It is shown that the involvement of the counter ion, chlorine, and the specific hydrogen bonds has noticeable effects on the Raman spectra of RhB that can partially explain the observed difference between Raman spectra of RhB in solution and on gold surfaces. It also indicates that an accurate description of surface enhanced Raman scattering for Rhodamine molecules on metal surface still requires to take into account the changes induced by the interracial interactions.展开更多
TiAl-based alloys have received extensive attention recently due to their excellent properties. However, the weak oxidation resistance at temperatures higher than 800℃ can limit their further high-temperature structu...TiAl-based alloys have received extensive attention recently due to their excellent properties. However, the weak oxidation resistance at temperatures higher than 800℃ can limit their further high-temperature structural applications.To improve the oxidation resistance of a high-Nb-content γ-TiAl alloy(Ti-45 Al-8.5 Nb, in units of at.%), a chromium(Cr)coating is prepared by using the plasma surface alloying technique, separately, at 800℃ and 1000℃. The x-ray diffraction(XRD) patterns reveal that an oxide surface layer consisting of Cr2O3, Al2O3, and TiO2 is produced on the Cr-coated Nb containing γ-TiAl substrates during the initial oxidation. However, the Cr2O3 is dominated in the oxide surface layer after being isothermally oxidized for 300 h. The oxidation kinetic curves are composed of a parabolic law stage(≤ 90 h) and a biquadratic law stage(≥ 90 h), fit by weight–gain curves. Due to diffusion in the fabrication process and oxidation process,the Cr-coated specimens have an adhesion force after being isothermally oxidized, specifically 69 N for a specimen after oxidation for 300 h. These results demonstrate that the Cr coating enhances the oxidation resistance and adhesion of a Ti-45 Al-8.5 Nb alloy, which may provide a new feasible scheme for designing oxidation protection layers.展开更多
BACKGROUND： Most of the reports on the prognostic indicators of patients with pancreatic adenocarcinoma are from developed countries. The present study focused on the prognostic indicators of Chinese patients with pa...BACKGROUND： Most of the reports on the prognostic indicators of patients with pancreatic adenocarcinoma are from developed countries. The present study focused on the prognostic indicators of Chinese patients with pancreatic adenocarcinoma. METHODS： A total of 300 patients with pancreatic adenocarcinoma who had undergone curative resection were included. The resection and R0/R1 resection rates for adenocarcinomas from different parts of the pancreas were calculated and clinical characteristics were analyzed.RESULTS： In 3427 patients diagnosed with pancreatic adenocarcinomas, only 300（8.8%） were eligible for radical resection. The total median survival of these patients was 19 months, and their 1-, 3-, and 5-year survival rates were 72.5%, 28.0% and 23.4%, respectively. The prognostic factors included socioeconomic status, smoking history, symptoms, high blood glucose, and various tumor characteristics, including perineural and vascular invasion, lymph node metastases, and CA19-9 levels before and after operation. Operation-associated prognostic indicators included operation time, blood loss and transfusions, pancreatic fistula, and complications. Independent predictors of mortality included poor socioeconomic status, smoking history, symptoms, CA19-9, perineural invasion and lymph node metastasis, grade of fistula and complications. Patient survival was not correlated with either resection margin or adjuvant chemotherapy in multivariate analysis.CONCLUSIONS： The survival rates of patients with curative resection for pancreatic adenocarcinoma in China are close to those in developed countries, but curative resection rate is far below. Socioeconomic status, symptoms, and CA19-9 are the three most prominent prognostic factors, which are helpful in patient selection and perioperative care.展开更多
Betatron radiation from laser wakefield accelerated electrons and X-rays scattered off a counter-propagating relativistic electron bunch arecollimated and hold the potential to extend the energy range to hard X-ray or...Betatron radiation from laser wakefield accelerated electrons and X-rays scattered off a counter-propagating relativistic electron bunch arecollimated and hold the potential to extend the energy range to hard X-ray or gamma ray band. The peak brightness of these incoherent radiations could reach the level of the brightest synchrotron light sources in the world due to their femtosecond pulse duration and source sizedown to a few micrometers. In this article, the principle and properties of these radiation sources are briefly reviewed and compared. Then wepresent our recent progress in betatron radiation enhancement in the perspective of both photon energy and photon number. The enhancement istriggered by using a clustering gas target, arousing a second injection of a fiercely oscillating electron bunch with large charge or stimulating aresonantly enhanced oscillation of the ionization injected electrons. By adopting these methods, bright photon source with energy over 100 keVis generated which would greatly impact applications such as nuclear physics, diagnostic radiology, laboratory astrophysics and high-energydensity science.展开更多
Dear Editor,This letter focuses on combining the respective advantages of cross-modality images which can compensate for the lack of information in the single modality.Meanwhile,due to the great appearance differences...Dear Editor,This letter focuses on combining the respective advantages of cross-modality images which can compensate for the lack of information in the single modality.Meanwhile,due to the great appearance differences between cross-modality image pairs,it often fails to make the feature representations of correspondences as close as possible.展开更多
Nowadays, machine learning is widely used in malware detection system as a core component. The machine learning algorithm is designed under the assumption that all datasets follow the same underlying data distribution...Nowadays, machine learning is widely used in malware detection system as a core component. The machine learning algorithm is designed under the assumption that all datasets follow the same underlying data distribution. But the real-world malware data distribution is not stable and changes with time. By exploiting the knowledge of the machine learning algorithm and malware data concept drift problem, we show a novel learning evasive botnet architecture and a stealthy and secure C&C mechanism. Based on the email communication channel, we construct a stealthy email-based P2 P-like botnet that exploit the excellent reputation of email servers and a huge amount of benign email communication in the same channel. The experiment results show horizontal correlation learning algorithm is difficult to separate malicious email traffic from normal email traffic based on the volume features and time-related features with enough confidence. We discuss the malware data concept drift and possible defense strategies.展开更多
基金supported by the National Natural Science Foundation of China(61903279)。
文摘Dear Editor,Since the existing hyperspectral image denoising methods suffer from excessive or incomplete denoising,leading to information distortion and loss,this letter proposes a deep denoising network in the frequency domain,termed D2Net.Our motivation stems from the observation that images from different hyperspectral image(HSI)bands share the same structural and contextual features while the reflectance variations in the spectra are mainly fallen on the details and textures.
基金supported by the Innovation Fund Project of Jiangxi Normal University(YJS2022065)the Domestic Visiting Program of Jiangxi Normal University.
文摘Mobile Edge Computing(MEC)is a technology designed for the on-demand provisioning of computing and storage services,strategically positioned close to users.In the MEC environment,frequently accessed content can be deployed and cached on edge servers to optimize the efficiency of content delivery,ultimately enhancing the quality of the user experience.However,due to the typical placement of edge devices and nodes at the network’s periphery,these components may face various potential fault tolerance challenges,including network instability,device failures,and resource constraints.Considering the dynamic nature ofMEC,making high-quality content caching decisions for real-time mobile applications,especially those sensitive to latency,by effectively utilizing mobility information,continues to be a significant challenge.In response to this challenge,this paper introduces FT-MAACC,a mobility-aware caching solution grounded in multi-agent deep reinforcement learning and equipped with fault tolerance mechanisms.This approach comprehensively integrates content adaptivity algorithms to evaluate the priority of highly user-adaptive cached content.Furthermore,it relies on collaborative caching strategies based onmulti-agent deep reinforcement learningmodels and establishes a fault-tolerancemodel to ensure the system’s reliability,availability,and persistence.Empirical results unequivocally demonstrate that FTMAACC outperforms its peer methods in cache hit rates and transmission latency.
基金supported by the National Natural Science Foundation of China(82170481)Anhui Natural Science Foundation(2008085J39 and 2108085MH314)+2 种基金Excellent Top-notch Talents Training Program of Anhui Universities(gxbjZD2022073)Anhui Province Innovation Team of Authentic Medicinal Materials Development and High Value Utilization(2022AH010080)Suzhou University Joint Cultivation Postgraduate Research Innovation Fund Project(2023KYCX04).
文摘Corona Virus Disease 2019(COVID-19)has brought the new challenges to scientific research.Isodon suzhouensis has good anti-inflammatory and antioxidant stress effects,which is considered as a potential treatment for COVID-19.The possibility for the treatment of COVID-19 with I.suzhouensis and its potential mechanism of action were explored by employing molecular docking and network pharmacology.Network pharmacology and molecular docking were used to screen drug targets,and lipopolysaccharide(LPS)induced RAW264.7 and NR8383 cells inflammation model was used for experimental verification.Collectively a total of 209 possible linkages against 18 chemical components from I.suzhouensis and 1194 COVID-19 related targets were selected.Among these,164 common targets were obtained from the intersection of I.suzhouensis and COVID-19.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enriched 582 function targets and 87 target proteins pathways,respectively.The results from molecular docking studies revealed that rutin,vitexin,isoquercitrin and quercetin had significant binding ability with 3 chymotrypsin like protease(3CLpro)and angiotensin converting enzyme 2(ACE2).In vitro studies showed that I.suzhouensis extract(ISE)may inhibit the activation of PI3K/Akt pathway and the expression level of downstream proinflammatory factors by inhibiting the activation of epidermal growth factor receptor(EGFR)in RAW264.7 cells induced by LPS.In addition,ISE was able to inhibit the activation of TLR4/NF-κB signaling pathway in NR8383 cells exposed to LPS.Overall,the network pharmacology and in vitro studies conclude that active components from I.suzhouensis have strong therapeutic potential against COVID-19 through multi-target,multi-pathway dimensions and can be a promising candidate against COVID-19.
文摘Mobile Edge Computing(MEC)is a promising technology that provides on-demand computing and efficient storage services as close to end users as possible.In an MEC environment,servers are deployed closer to mobile terminals to exploit storage infrastructure,improve content delivery efficiency,and enhance user experience.However,due to the limited capacity of edge servers,it remains a significant challenge to meet the changing,time-varying,and customized needs for highly diversified content of users.Recently,techniques for caching content at the edge are becoming popular for addressing the above challenges.It is capable of filling the communication gap between the users and content providers while relieving pressure on remote cloud servers.However,existing static caching strategies are still inefficient in handling the dynamics of the time-varying popularity of content and meeting users’demands for highly diversified entity data.To address this challenge,we introduce a novel method for content caching over MEC,i.e.,PRIME.It synthesizes a content popularity prediction model,which takes users’stay time and their request traces as inputs,and a deep reinforcement learning model for yielding dynamic caching schedules.Experimental results demonstrate that PRIME,when tested upon the MovieLens 1M dataset for user request patterns and the Shanghai Telecom dataset for user mobility,outperforms its peers in terms of cache hit rates,transmission latency,and system cost.
基金Project supported by the Shandong Provincial Natural Science Foundation,China(Grant Nos.ZR2022MA025 and ZR2020MA077).
文摘The possible configurations of pyrrole absorbed on a Si(100)surface have been investigated by x-ray photoelectron spectroscopy(XPS)and near-edge x-ray absorption fine structure(NEXAFS)spectra.The C-1s XPS and NEXAFS spectra of these adsorption configurations have been calculated by using the density functional theory(DFT)method and fullcore hole(FCH)approximation to investigate the relationship between the adsorption configurations and the spectra.The result shows that the XPS and NEXAFS spectra are structurally dependent on the configurations of pyrrole absorbed on the Si(100)surface.Compared with the XPS,the NEXAFS spectra are relatively sensitive to the adsorption configurations and can accurately identify them.The NEXAFS decomposition spectra produced by non-equivalent carbon atoms have also been calculated and show that the spectral features vary with the diverse types of carbon atoms and their structural environments.
基金the National Natural Science Foundation of China under Grant 62075169,Grant 62003247,and Grant 62061160370the Hubei Province Key Research and Development Program under Grant 2021BBA235the Zhuhai Basic and Applied Basic Research Foundation under Grant ZH22017003200010PWC.
文摘The rotary motion deblurring is an inevitable procedure when the imaging seeker is mounted in the rotating missiles.Traditional rotary motion deblurring methods suffer from ringing artifacts and noise,especially for large blur extents.To solve the above problems,we propose a progressive rotary motion deblurring framework consisting of a coarse deblurring stage and a refinement stage.In the first stage,we design an adaptive blur extents factor(BE factor)to balance noise suppression and details reconstruction.And a novel deconvolution model is proposed based on BE factor.In the second stage,a triplescale deformable module CNN(TDM-CNN)is designed to reduce the ringing artifacts,which can exploit the 2D information of an image and adaptively adjust spatial sampling locations.To establish a standard evaluation benchmark,a real-world rotary motion blur dataset is proposed and released,which includes rotary blurred images and corresponding ground truth images with different blur angles.Experimental results demonstrate that the proposed method outperforms the state-of-the-art models on synthetic and real-world rotary motion blur datasets.The code and dataset are available at https://github.com/JinhuiQin/RotaryDeblurring.
基金the National Natural Science Foundation of China under Grant No.62272087Science and Technology Planning Project of Sichuan Province under Grant No.2023YFG0161.
文摘Long-term urban traffic flow prediction is an important task in the field of intelligent transportation,as it can help optimize traffic management and improve travel efficiency.To improve prediction accuracy,a crucial issue is how to model spatiotemporal dependency in urban traffic data.In recent years,many studies have adopted spatiotemporal neural networks to extract key information from traffic data.However,most models ignore the semantic spatial similarity between long-distance areas when mining spatial dependency.They also ignore the impact of predicted time steps on the next unpredicted time step for making long-term predictions.Moreover,these models lack a comprehensive data embedding process to represent complex spatiotemporal dependency.This paper proposes a multi-scale persistent spatiotemporal transformer(MSPSTT)model to perform accurate long-term traffic flow prediction in cities.MSPSTT adopts an encoder-decoder structure and incorporates temporal,periodic,and spatial features to fully embed urban traffic data to address these issues.The model consists of a spatiotemporal encoder and a spatiotemporal decoder,which rely on temporal,geospatial,and semantic space multi-head attention modules to dynamically extract temporal,geospatial,and semantic characteristics.The spatiotemporal decoder combines the context information provided by the encoder,integrates the predicted time step information,and is iteratively updated to learn the correlation between different time steps in the broader time range to improve the model’s accuracy for long-term prediction.Experiments on four public transportation datasets demonstrate that MSPSTT outperforms the existing models by up to 9.5%on three common metrics.
基金Supported by National Natural Science Foundation of China(No.82271119)Shanghai Rising-Star Program(No.23QA1401000)+1 种基金Healthy Young Talents Project of Shanghai Municipal Health Commission(No.2022YQ015)Project of Shanghai Science and Technology(No.21Y11909800).
文摘Dear Editor,We report a case with trans-photorefractive keratectomy(PRK)for recurrent epithelial corneal erosion caused by cooking oil after EVO-implantable contact lens(ICL)(EVO Visian ICL;STAAR Surgical AG,Switzerland),which should be distinguished from postoperative complications of EVO-ICL.Most corneal burns are classified as chemical and thermal burns,referring to direct contact injury to the cornea.
基金This work was supported by the National Natural Science Foundation of China(62075169,62003247,62061160370)the Key Research and Development Program of Hubei Province(2020BAB113).
文摘This study proposes a novel general image fusion framework based on cross-domain long-range learning and Swin Transformer,termed as SwinFusion.On the one hand,an attention-guided cross-domain module is devised to achieve sufficient integration of complementary information and global interaction.More specifically,the proposed method involves an intra-domain fusion unit based on self-attention and an interdomain fusion unit based on cross-attention,which mine and integrate long dependencies within the same domain and across domains.Through long-range dependency modeling,the network is able to fully implement domain-specific information extraction and cross-domain complementary information integration as well as maintaining the appropriate apparent intensity from a global perspective.In particular,we introduce the shifted windows mechanism into the self-attention and cross-attention,which allows our model to receive images with arbitrary sizes.On the other hand,the multi-scene image fusion problems are generalized to a unified framework with structure maintenance,detail preservation,and proper intensity control.Moreover,an elaborate loss function,consisting of SSIM loss,texture loss,and intensity loss,drives the network to preserve abundant texture details and structural information,as well as presenting optimal apparent intensity.Extensive experiments on both multi-modal image fusion and digital photography image fusion demonstrate the superiority of our SwinFusion compared to the state-of-theart unified image fusion algorithms and task-specific alternatives.Implementation code and pre-trained weights can be accessed at https://github.com/Linfeng-Tang/SwinFusion.
基金supported by the National Natural Science Foundation of China(62276192,62075169,62061160370)the Key Research and Development Program of Hubei Province(2020BAB113)。
文摘Image fusion aims to integrate complementary information in source images to synthesize a fused image comprehensively characterizing the imaging scene. However, existing image fusion algorithms are only applicable to strictly aligned source images and cause severe artifacts in the fusion results when input images have slight shifts or deformations. In addition,the fusion results typically only have good visual effect, but neglect the semantic requirements of high-level vision tasks.This study incorporates image registration, image fusion, and semantic requirements of high-level vision tasks into a single framework and proposes a novel image registration and fusion method, named Super Fusion. Specifically, we design a registration network to estimate bidirectional deformation fields to rectify geometric distortions of input images under the supervision of both photometric and end-point constraints. The registration and fusion are combined in a symmetric scheme, in which while mutual promotion can be achieved by optimizing the naive fusion loss, it is further enhanced by the mono-modal consistent constraint on symmetric fusion outputs. In addition, the image fusion network is equipped with the global spatial attention mechanism to achieve adaptive feature integration. Moreover, the semantic constraint based on the pre-trained segmentation model and Lovasz-Softmax loss is deployed to guide the fusion network to focus more on the semantic requirements of high-level vision tasks. Extensive experiments on image registration, image fusion,and semantic segmentation tasks demonstrate the superiority of our Super Fusion compared to the state-of-the-art alternatives.The source code and pre-trained model are publicly available at https://github.com/Linfeng-Tang/Super Fusion.
基金the Chinese Medicine Administration Bureau of Jiangsu Province,No.HD5072
文摘BACKGROUND： Trauma can damage the spinal cord or cauda equina to different degrees. Previous studies have verified that traditional Chinese medicine has effects on spinal cord injury via a variety of pathways. OBJECTIVE： To observe changes in hemorheology and inflammatory factors in spinal cord injury rats following treatment with the Chinese medicine Jisuikang, to verify the dose-dependent effect of Jisuikang, and to compare its effects with the effects of prednisone. DESIGN, TIME AND SETTING： A randomized study was performed at the Research Institute of Orthopedics, and Experimental Center of First Clinical Medical College, Nanjing University of Traditional Chinese Medicine, China from September 2007 to March 2008. MATERIALS： Jisuikang powdered extract, composed of milkvetch root （30 g）, Chinese angelica （12 g）, red peony root （12 g）, earthworm （10 g）, szechwan lovage rhizome （10 g）, peach seed （10 g） and safflower （10 g） was provided by the Experimental Center, First Clinical Medical College, Nanjing University of Traditional Chinese medicine. Each gram of powdered extract was equivalent to 6.47 g crude drug. METHODS： A total of 72 Sprague Dawley rats were randomly assigned into 6 groups （n = 12）. Rat models of spinal cord injury were established using the occlusion method. Rats in the model group were treated with distilled water. Rats in the 25 g/kg, 12.5 g/kg, and 6.25 g/kg Jisuikang groups were given 25 g＆g, 12.5 g/kg, or 6.25 g/kg Jisuikang by gavage, for 14 days. Rats in the prednisone group received 0.06 g/kg prednisone by gavage, for 7 days. Rats in the normal group were given the same volume of distilled water. The volume of administration was 15 mL/kg. MAIN OUTCOME MEASURES： Rat serum interleukin-10, tumor necrosis factor- α （TNF-α ）, nitric oxide, nitric oxide synthase levels, malondialdehyde content, superoxide dismutase activity and whole blood viscosity were measured in each group. Spinal cord around the site of the model was collected. Half the spinal cord was used for histopathologic examination. The other half was used for measurement of nitric oxide and NOS levels, malondialdehyde contents, and superoxide dismutase activity. RESULTS： Superoxide dismutase activity was higher in the 25 g/kg Jisuikang group than in the model group Malondialdehyde contents, nitric oxide and NOS levels were lower in the 25 g/kg and 12.5 g/kg Jisuikang groups compared with the model group. Whole blood viscosity was lower in the 25 g/kg and 12.5 g/kg Jisuikang groups compared with the model group （P 〈 0.05-0.01）. Serum TNF- α content was lower in each Jisuikang group compared with the model group （P 〈 0.05-0.01）. Serum interleukin-10 levels were greater in the prednisone group and each Jisuikang group compared with the model group （P 〈 0.01）. Mild hemorrhage and necrosis in the rat spinal cord, and unclear neural cell swelling were seen in the 25 g/kg Jisuikang group： Severe hemorrhage and necrosis in the rat spinal cord, and distinct neural cell swelling were seen in the 12.5 g/kg Jisuikang group. Edema in the white matter was found in the 6.25 g/kg Jisuikang group. Pathological changes in the prednisone group were identical to the 25 g/kg and 12.5 g/kg Jisuikang groups. CONCLUSION： Jisuikang inhibits nitric oxide synthase expression, reduces nitric oxide and TNF-α levels decreases malondialdehyde content, increases interleukin-10 levels and superoxide dismutase activity, improves indices of hemorheology, and prevents secondary changes in spinal cord injury, resulting in relieving pathological changes in spinal cord tissue. The outcome was significant in the 25 g/kg Jisuikang group compared with the 12.5 g/kg Jisuikang group.
基金supported by research on value model and technology application of patent operation of science and technology project(52094020000U)National Natural Science Foundation of China(52177193).
文摘The technology deployed for lithium-ion battery state of charge(SOC)estimation is an important part of the design of electric vehicle battery management systems.Accurate SOC estimation can forestall excessive charging and discharging of lithium-ion batteries,thereby improving discharge efficiency and extending cycle life.In this study,the key lithium-ion battery SOC estimation technologies are summarized.First,the research status of lithium-ion battery modeling is introduced.Second,the main technologies and difficulties in model parameter identification for lithium-ion batteries are discussed.Third,the development status and advantages and disadvantages of SOC estimation methods are summarized.Finally,the current research problems and prospects for development trends are summarized.
基金supported by the National Natural Science Foundation of China under Grant 62003247, Grant 62075169, and Grant 62061160370。
文摘Infrared(IR) small target detection is one of the key technologies of infrared search and track(IRST)systems. Existing methods have some limitations in detection performance, especially when the target size is irregular or the background is complex. In this paper, we propose a pixel-level local contrast measure(PLLCM), which can subdivide small targets and backgrounds at pixel level simultaneously.With pixel-level segmentation, the difference between the target and the background becomes more obvious, which helps to improve the detection performance. First, we design a multiscale sliding window to quickly extract candidate target pixels. Then, a local window based on random walker(RW) is designed for pixel-level target segmentation. After that, PLLCM incorporating probability weights and scale constraints is proposed to accurately measure local contrast and suppress various types of background interference. Finally, an adaptive threshold operation is applied to separate the target from the PLLCM enhanced map. Experimental results show that the proposed method has a higher detection rate and a lower false alarm rate than the baseline algorithms, while achieving a high speed.
文摘Dear Editor,3×3 Infrared imaging,generally,of low quality,plays an important role in security surveillance and target detection.In this letter,we improve the quality of infrared images by combining both hardware and software.To this end,an infrared light field imaging enhancement system is built for the first time,including a infrared light field imaging device,a large-scale infrared light field dataset(IRLF-WHU),and a progressive fusion network for infrared image enhancement(IR-PFNet).
基金ACKNOWLEDGMENTS This work is supported by China Postdoctoral Science Foundation （No.2013M541951）. The Swedish National Infrastructure for Computing （SNIC） is acknowledged for computer time.
文摘Rhodamine molecules are one of the most used dyes for applications related to Raman spectroscopy. We have systematically studied Raman spectra of Rhodamine 6G, Rhodamine 123, and Rhodamine B （RhB） molecules using density functional theory. It is found that with BP86 functional the calculated Raman spectra of cationic Rhodamine molecules are in good agreement with corresponding experimental spectra in aqueous solution. It is shown that the involvement of the counter ion, chlorine, and the specific hydrogen bonds has noticeable effects on the Raman spectra of RhB that can partially explain the observed difference between Raman spectra of RhB in solution and on gold surfaces. It also indicates that an accurate description of surface enhanced Raman scattering for Rhodamine molecules on metal surface still requires to take into account the changes induced by the interracial interactions.
基金Project supported by the National Natural Science Foundation of China(Grant No.51601122)the 2019–2020 Intergovernmental Cooperation Projects in Science and Technology of the Ministry of Science and Technology,China(Grant No.CB02-03)+3 种基金the Science and Technology Major Project of Shanxi Province,China(Grant No.20181102013)the“331 Project”Engineering Research Center of Shanxi Province,China(Grant No.PT201801)the China Postdoctoral Science Foundation(Grant No.2017M620574)the Fund from the State Key Laboratory of Advanced Metal Materials,China(Grant No.2019-ZD02).
文摘TiAl-based alloys have received extensive attention recently due to their excellent properties. However, the weak oxidation resistance at temperatures higher than 800℃ can limit their further high-temperature structural applications.To improve the oxidation resistance of a high-Nb-content γ-TiAl alloy(Ti-45 Al-8.5 Nb, in units of at.%), a chromium(Cr)coating is prepared by using the plasma surface alloying technique, separately, at 800℃ and 1000℃. The x-ray diffraction(XRD) patterns reveal that an oxide surface layer consisting of Cr2O3, Al2O3, and TiO2 is produced on the Cr-coated Nb containing γ-TiAl substrates during the initial oxidation. However, the Cr2O3 is dominated in the oxide surface layer after being isothermally oxidized for 300 h. The oxidation kinetic curves are composed of a parabolic law stage(≤ 90 h) and a biquadratic law stage(≥ 90 h), fit by weight–gain curves. Due to diffusion in the fabrication process and oxidation process,the Cr-coated specimens have an adhesion force after being isothermally oxidized, specifically 69 N for a specimen after oxidation for 300 h. These results demonstrate that the Cr coating enhances the oxidation resistance and adhesion of a Ti-45 Al-8.5 Nb alloy, which may provide a new feasible scheme for designing oxidation protection layers.
基金supported in part by grants from the National Natural Scientific Foundation of China(81270527)the Health Industry Special Projects of Research(201202007)the Scientific Foundation of the First Affiliated Hospital of Harbin Medical University(2014B15)
文摘BACKGROUND： Most of the reports on the prognostic indicators of patients with pancreatic adenocarcinoma are from developed countries. The present study focused on the prognostic indicators of Chinese patients with pancreatic adenocarcinoma. METHODS： A total of 300 patients with pancreatic adenocarcinoma who had undergone curative resection were included. The resection and R0/R1 resection rates for adenocarcinomas from different parts of the pancreas were calculated and clinical characteristics were analyzed.RESULTS： In 3427 patients diagnosed with pancreatic adenocarcinomas, only 300（8.8%） were eligible for radical resection. The total median survival of these patients was 19 months, and their 1-, 3-, and 5-year survival rates were 72.5%, 28.0% and 23.4%, respectively. The prognostic factors included socioeconomic status, smoking history, symptoms, high blood glucose, and various tumor characteristics, including perineural and vascular invasion, lymph node metastases, and CA19-9 levels before and after operation. Operation-associated prognostic indicators included operation time, blood loss and transfusions, pancreatic fistula, and complications. Independent predictors of mortality included poor socioeconomic status, smoking history, symptoms, CA19-9, perineural invasion and lymph node metastasis, grade of fistula and complications. Patient survival was not correlated with either resection margin or adjuvant chemotherapy in multivariate analysis.CONCLUSIONS： The survival rates of patients with curative resection for pancreatic adenocarcinoma in China are close to those in developed countries, but curative resection rate is far below. Socioeconomic status, symptoms, and CA19-9 are the three most prominent prognostic factors, which are helpful in patient selection and perioperative care.
基金This work was supported by the National Basic Research Program of China(2013CBA01500)the National Key Scientific Instrument and Equipment Development Project(2012YQ120047)+1 种基金the National Natural Science Foundation of China(11334013,11421064,11374210,and 11305185)the CAS Key Program(KGZD-EW-T05).
文摘Betatron radiation from laser wakefield accelerated electrons and X-rays scattered off a counter-propagating relativistic electron bunch arecollimated and hold the potential to extend the energy range to hard X-ray or gamma ray band. The peak brightness of these incoherent radiations could reach the level of the brightest synchrotron light sources in the world due to their femtosecond pulse duration and source sizedown to a few micrometers. In this article, the principle and properties of these radiation sources are briefly reviewed and compared. Then wepresent our recent progress in betatron radiation enhancement in the perspective of both photon energy and photon number. The enhancement istriggered by using a clustering gas target, arousing a second injection of a fiercely oscillating electron bunch with large charge or stimulating aresonantly enhanced oscillation of the ionization injected electrons. By adopting these methods, bright photon source with energy over 100 keVis generated which would greatly impact applications such as nuclear physics, diagnostic radiology, laboratory astrophysics and high-energydensity science.
基金supported by the National Natural Science Foundation of China(NSFC)(62003247,62075169,62061160370)。
文摘Dear Editor,This letter focuses on combining the respective advantages of cross-modality images which can compensate for the lack of information in the single modality.Meanwhile,due to the great appearance differences between cross-modality image pairs,it often fails to make the feature representations of correspondences as close as possible.
基金the National Key Basic Research Program of China (Grant: 2013CB834204)the National Natural Science Foundation of China (Grant: 61300242, 61772291)+1 种基金the Tianjin Research Program of Application Foundation and Advanced Technology (Grant: 15JCQNJC41500, 17JCZDJC30500)the Open Project Foundation of Information Security Evaluation Center of Civil Aviation, Civil Aviation University of China (Grant: CAAC-ISECCA- 201701, CAAC-ISECCA-201702)
文摘Nowadays, machine learning is widely used in malware detection system as a core component. The machine learning algorithm is designed under the assumption that all datasets follow the same underlying data distribution. But the real-world malware data distribution is not stable and changes with time. By exploiting the knowledge of the machine learning algorithm and malware data concept drift problem, we show a novel learning evasive botnet architecture and a stealthy and secure C&C mechanism. Based on the email communication channel, we construct a stealthy email-based P2 P-like botnet that exploit the excellent reputation of email servers and a huge amount of benign email communication in the same channel. The experiment results show horizontal correlation learning algorithm is difficult to separate malicious email traffic from normal email traffic based on the volume features and time-related features with enough confidence. We discuss the malware data concept drift and possible defense strategies.
