Once more to the lake is a representative work of the American Writer, Elwyn Brooks White, and has been acclaimed by people in the world. The paper offers a three-layered contrasting analysis of the essay. By detailed...Once more to the lake is a representative work of the American Writer, Elwyn Brooks White, and has been acclaimed by people in the world. The paper offers a three-layered contrasting analysis of the essay. By detailed analysis of the contrasts running through the whole essay, the author finds that those contrasts are symbol of White's internal struggle and reflection for life.On the foundation of the three-layered contrasts, the paper presents the theme analysis and clarifies the content of the essay.展开更多
Using the monthly geopotential heights and winds for 700 and 200 hPa for India during July and August, and the weekly M-100 Soviet rocketsonde temperature and wind data for Thumba (8.5 ° N, 76.9 ° E) during ...Using the monthly geopotential heights and winds for 700 and 200 hPa for India during July and August, and the weekly M-100 Soviet rocketsonde temperature and wind data for Thumba (8.5 ° N, 76.9 ° E) during the last week of June and the first week of September for the two contrasting summer monsoon years 1975 (a very strong monsoon year) and 1979 (a very weak monsoon year), a study has been made to examine the mean circulation features of the troposphere over India, and the structures of the temperatures and the winds of the middle atmosphere over Thumba. The study suggested that the axis of the monsoon trough (AMT) at 700 hPa shifted southward in 1975 and northward towards the foothills of the Himalayas in 1979, from its normal position. Superimposed on the low-pressure area (AMT) at 700 hPa, a well-defined divergence was noticed at 200 hPa over the northern India in 1975.The mean temperatures at 25,50 and 60 km (middle atmosphere) over Thumba were cooler in 1975 than in 1979. While a cooling trend in 1975 and warming trend in 1979 were observed at 25 and 50 km, a reversed picture was noticed at 60 km. There was a weak easterly / westerly (weak westerly phase) zonal wind in 1975 and a strong easterly zonal wind in 1979. A phase reversal of the zonal wind was observed at 50 km. A tentative physical mechanism was offered, in terms of upward propagation of the two equatorially trapped planetary waves i.e. the Kelvin and the mixed Rossby-gravity waves, to explain the occurrence of the two spells of strong warmings in the mesosphere in 1975.展开更多
The iconic image of a giant radiating dyke swarm subsequently fragmented into three pieces via supercontinental breakup was produced by Paul May in1971(see next page).That figure presented a large part of
As the risk of malware is sharply increasing in Android platform,Android malware detection has become an important research topic.Existing works have demonstrated that required permissions of Android applications are ...As the risk of malware is sharply increasing in Android platform,Android malware detection has become an important research topic.Existing works have demonstrated that required permissions of Android applications are valuable for malware analysis,but how to exploit those permission patterns for malware detection remains an open issue.In this paper,we introduce the contrasting permission patterns to characterize the essential differences between malwares and clean applications from the permission aspect Then a framework based on contrasting permission patterns is presented for Android malware detection.According to the proposed framework,an ensemble classifier,Enclamald,is further developed to detect whether an application is potentially malicious.Every contrasting permission pattern is acting as a weak classifier in Enclamald,and the weighted predictions of involved weak classifiers are aggregated to the final result.Experiments on real-world applications validate that the proposed Enclamald classifier outperforms commonly used classifiers for Android Malware Detection.展开更多
The Awakening is about the heroine Edna Pontellier awakes and tries to reset her relation with the world in New Orleans,a place the family chose to spend the summer, where there also are influences working their way t...The Awakening is about the heroine Edna Pontellier awakes and tries to reset her relation with the world in New Orleans,a place the family chose to spend the summer, where there also are influences working their way to awake Edna. Among them, theeffects from Madame Ratignolle and Madame Reisz are of great importance in the process of Edna's awakening and to her final sui-cide. This dissertation will see how Edna is affected by and distinguished from them, and get the conclusion that Edna fails being alife mediator by contrasting with the two women.展开更多
Laser wakefield accelerators(LWFAs)offer acceleration gradients up to 1000 times higher than those of conventional radio-frequency accelerators,offering a pathway to significantly more compact and cost-effective accel...Laser wakefield accelerators(LWFAs)offer acceleration gradients up to 1000 times higher than those of conventional radio-frequency accelerators,offering a pathway to significantly more compact and cost-effective accelerator systems.This breakthrough opens up new possibilities for laboratory-scale light sources.All-optical inverse Compton scattering(AOCS)sources driven by LWFAs produce high-brightness,quasimonochromatic X rays with micrometer-scale source sizes,delivering the spatial coherence and resolution required for X-ray phase-contrast imaging(XPCI).These features position AOCS X-ray sources as promising tools for applications in biology,medicine,physics,and materials science.However,previous AOCS-based imaging studies have primarily focused on X-ray absorption imaging.In this work,we report successful experimental demonstrations of edge-enhanced in-line XPCI using energy-tunable,quasi-monochromatic AOCS X rays.With a spatial resolution of~20μm,our results clearly show the potential of high-resolution,AOCS-based XPCI applications.展开更多
Drill string vibration during drilling plays a vital and potentially decisive role in maintaining wellbore stability,as repeated impacts may lead to fatigue and borehole collapse.While drilling through geological laye...Drill string vibration during drilling plays a vital and potentially decisive role in maintaining wellbore stability,as repeated impacts may lead to fatigue and borehole collapse.While drilling through geological layers,a material contrast may act as a localization point for wellbore damage.The hypothesis tested in this paper is that wellbore instability is focused on the boundary between the layers and that mechanical contrasts accelerate the wellbore collapse.In this study,an elastic-plastic damage model was employed to investigate the effects of repeated mechanical impacts on wellbore stability.A 2-dimensional(2D)model of a wellbore surrounded by contrasting materials was developed,and the accumulated damage caused by repeated lateral impacts was monitored.It was found that damage develops not only around the wall of the wellbore but also along the material boundaries.A sensitivity analysis was carried out to identify the impact of contrasts in both elastic(Young's modulus and Poisson's ratio)and plastic(cohesion,friction angle,and dilation angle)parameters between layers.Four damage patterns were identifiedin the simulated models.The results also suggested that the number of impacts required to reach the critical damage was highly affected by the contrast in elastic parameters,while cohesion and friction angle contrasts had a lesser effect.Additionally,increasing the contrast in the dilation angle localized the damage,thus reducing the number of impacts required to trigger wellbore failure.展开更多
In high-intensity electromagnetic warfare,radar systems are persistently subjected to multi-jammer attacks,including potentially novel unknown jamming types that may emerge exclusively under wartime conditions.These j...In high-intensity electromagnetic warfare,radar systems are persistently subjected to multi-jammer attacks,including potentially novel unknown jamming types that may emerge exclusively under wartime conditions.These jamming signals severely degrade radar detection performance.Precise recognition of these unknown and compound jamming signals is critical to enhancing the anti-jamming capabilities and overall reliability of radar systems.To address this challenge,this article proposes a novel open-set compound jamming cognition(OSCJC)method.The proposed method employs a detection-classification dual-network architecture,which not only overcomes the false alarm and misdetection issues of traditional closed-set recognition methods when dealing with unknown jamming but also effectively addresses the performance bottleneck of existing open-set recognition techniques focusing on single jamming scenarios in compound jamming environments.To achieve unknown jamming detection,we first employ a consistency labeling strategy to train the detection network using diverse known jamming samples.This strategy enables the network to acquire highly generalizable jamming features,thereby accurately localizing candidate regions for individual jamming components within compound jamming.Subsequently,we introduce contrastive learning to optimize the classification network,significantly enhancing both intra-class clustering and inter-class separability in the jamming feature space.This method not only improves the recognition accuracy of the classification network for known jamming types but also enhances its sensitivity to unknown jamming types.Simulations and experimental data are used to verify the effectiveness of the proposed OSCJC method.Compared with the state-of-the-art open-set recognition methods,the proposed method demonstrates superior recognition accuracy and enhanced environmental adaptability.展开更多
To address the issue of scarce labeled samples and operational condition variations that degrade the accuracy of fault diagnosis models in variable-condition gearbox fault diagnosis,this paper proposes a semi-supervis...To address the issue of scarce labeled samples and operational condition variations that degrade the accuracy of fault diagnosis models in variable-condition gearbox fault diagnosis,this paper proposes a semi-supervised masked contrastive learning and domain adaptation(SSMCL-DA)method for gearbox fault diagnosis under variable conditions.Initially,during the unsupervised pre-training phase,a dual signal augmentation strategy is devised,which simultaneously applies random masking in the time domain and random scaling in the frequency domain to unlabeled samples,thereby constructing more challenging positive sample pairs to guide the encoder in learning intrinsic features robust to condition variations.Subsequently,a ConvNeXt-Transformer hybrid architecture is employed,integrating the superior local detail modeling capacity of ConvNeXt with the robust global perception capability of Transformer to enhance feature extraction in complex scenarios.Thereafter,a contrastive learning model is constructed with the optimization objective of maximizing feature similarity across different masked instances of the same sample,enabling the extraction of consistent features from multiple masked perspectives and reducing reliance on labeled data.In the final supervised fine-tuning phase,a multi-scale attention mechanism is incorporated for feature rectification,and a domain adaptation module combining Local Maximum Mean Discrepancy(LMMD)with adversarial learning is proposed.This module embodies a dual mechanism:LMMD facilitates fine-grained class-conditional alignment,compelling features of identical fault classes to converge across varying conditions,while the domain discriminator utilizes adversarial training to guide the feature extractor toward learning domain-invariant features.Working in concert,they markedly diminish feature distribution discrepancies induced by changes in load,rotational speed,and other factors,thereby boosting the model’s adaptability to cross-condition scenarios.Experimental evaluations on the WT planetary gearbox dataset and the Case Western Reserve University(CWRU)bearing dataset demonstrate that the SSMCL-DA model effectively identifies multiple fault classes in gearboxes,with diagnostic performance substantially surpassing that of conventional methods.Under cross-condition scenarios,the model attains fault diagnosis accuracies of 99.21%for the WT planetary gearbox and 99.86%for the bearings,respectively.Furthermore,the model exhibits stable generalization capability in cross-device settings.展开更多
Cerebral ischemia restricts cerebral blood flow(CBF),leading to unstable hemodynamics.Past studies of ischemia mainly focused on cortical CBF reduction.However,its impact on hemodynamic changes,especially temporal var...Cerebral ischemia restricts cerebral blood flow(CBF),leading to unstable hemodynamics.Past studies of ischemia mainly focused on cortical CBF reduction.However,its impact on hemodynamic changes,especially temporal varying characteristics,remains poorly understood.Here,we collected cortical resting-state CBF in rats with left carotid artery blockage during occlusion–reperfusion,and measured the temporal variability and changes in laterality using a novel state-space method.This method was also applied to stroke EEG datasets to validate its effectiveness.After arterial occlusion,the left marginal motor,sensory,auditory,and visual cortices exhibited severe temporal variability impairments.The laterality analysis indicated that affected left regions showed inferior unilateral mean,inter-hemispheric transition probability,time fraction,and laterality duration,while the right side had a higher laterality time fraction and duration.These impairments recovered partially following blood flow restoration.Besides,the ischemic state-space metrics were positively correlated with the pre-occlusion baseline appearance.Stroke patients exhibited impaired temporal variability in the affected ischemic hemisphere.The state-space analysis revealed damaged CBF temporal variability during cerebral ischemia and predicted baseline-ischemia connections.展开更多
This study aims to develop a novel,cost-effective method for fabricating silicone vascular phantoms(SVPs)using"chewy candy"as a dissolvable core material.The study explores the feasibility of using chewy can...This study aims to develop a novel,cost-effective method for fabricating silicone vascular phantoms(SVPs)using"chewy candy"as a dissolvable core material.The study explores the feasibility of using chewy candy to create detailed and intricate vascular models for clinical applications.The chewy candy,an amorphous material,was manually extruded to form vascular models of varying diameters.These models were embedded in a silicone mixture,which was then cured.The chewy candy was subsequently dissolved,leaving behind hollow silicone vascular channels.The SVPs were evaluated for their morphological accuracy and functionality through laser speckle contrast imaging.The SVPs successfully replicated vascular channels with consistent diameters,demonstrating minimal variation across different regions.Functional evaluation using laser speckle contrast imaging revealed distinct flow dynamics in Y-shaped and H-shaped SVPs,highlighting the potential for these phantoms to simulate realistic fluid dynamics in vascular systems.This study presents a simple,time-saving,and innovative approach to fabricating complex 3D SVPs using chewy candy.This method offers a viable alternative to traditional fabrication techniques,with potential applications in various biomedical fields.展开更多
Adjuvants enhance and prolong the immune response to therapeutic agents,such as drugs and vaccines.However,conventional adjuvants have limitations in terms of immune specificity and duration.Nanoadjuvants can leverage...Adjuvants enhance and prolong the immune response to therapeutic agents,such as drugs and vaccines.However,conventional adjuvants have limitations in terms of immune specificity and duration.Nanoadjuvants can leverage their nanoscale size to increase the capture efficacy of antigens by antigen-presenting cells and improve immunogen presentation for targeted delivery.Furthermore,noninvasive visualization of bifunctional nanoadjuvants with integrated efficacy and imaging postdelivery can provide insights into in vivo distribution and performance,aiding in the optimization and design of new dosage forms.This review systematically summarizes the structure,assembly,and function of nanoadjuvants alongside contrast agents.It delves into the impact of complex structures formed by nanoadjuvant-contrast agent interactions on antigen presentation,migration,imaging tracking,and visualization of immune cell recruitment.It also discusses how imaging can determine optimal immune intervals,vaccine safety,and toxicity while enabling diagnostic and therapeutic integration.Moreover,this paper discusses potential applications of novel adjuvants and promising imaging technologies that could have implications for future vaccine and drug development endeavors.展开更多
Medical imaging is essential in modern health care,allowing accurate diagnosis and effective treatment planning.These images,however,often demonstrate low contrast,noise,and brightness distortion that reduce their dia...Medical imaging is essential in modern health care,allowing accurate diagnosis and effective treatment planning.These images,however,often demonstrate low contrast,noise,and brightness distortion that reduce their diagnostic reliability.This review presents a structured and comprehensive analysis of advanced histogram equalization(HE)-based techniques for medical image enhancement.Our review methodology encompasses:(1)classical HE approaches and related limitations in medical domains;(2)adaptive schemes like Adaptive Histogram Equalization(AHE)and Contrast Limited Adaptive Histogrma Equalization(CLAHE)and their advance variants;(3)brightnesspreserving schemes like BBHE and MMBEBHE and related algorithms;(4)dynamic and recursive histogram equalization methods incorporating DHE and RMSHE;(5)fuzzy logic-based enhancement methodologies addressing uncertainty and noise in medical images;and(6)hybrid optimization methodologies through the application of metaheuristic algorithms(World Cup Optimization,Particle Swarm Optimization,Genetic Algorithms,along with histogram-based methodologies.)There is also a comparative discussion given based on contrast improvement,image brightness preservation,noise management,and computational efficiency.Such advancements have better capabilities of improving image quality,which is more important for improved diagnosis and image analysis.展开更多
Global land monsoon precipitation(GLMP)is highly sensitive to changes in interhemispheric thermal contrast(ITC).Amplified interhemispheric asymmetries of GLMP due to enhanced ITC driven by high-level anthropogenic emi...Global land monsoon precipitation(GLMP)is highly sensitive to changes in interhemispheric thermal contrast(ITC).Amplified interhemispheric asymmetries of GLMP due to enhanced ITC driven by high-level anthropogenic emissions are expected to simultaneously increase the probability of regional floods and droughts,threatening ecosystems within global terrestrial monsoon regions and the freshwater supply for billions of residents in these areas.In this study,the responses of GLMP to the evolution of ITC toward the carbon neutrality goal are assessed using multimodel outputs from a new model intercomparison project(CovidMIP).The results show that the Northern Hemisphere-Southern Hemisphere(NH-SH)asymmetry of GLMP in boreal summer weakens during the 2040s,as a persistent reduction in well-mixed greenhouse gas(WMGHG)emissions leads to a downward trend in the ITC after 2040.At the same time,the reduction in WMGHG emissions dampens the Eastern Hemisphere-Western Hemisphere(EH-WH)asymmetry of GLMP by inducing La Niña-like cooling and enhancing moisture transport to Inner America.The resulting increases in land monsoon precipitation(LMP)may alleviate drought under the global warming scenario by about 19%-25%and 7%-9%in the WH and SH monsoon regions,respectively.However,a persistent reduction in aerosol emissions in Asia will dominate the increases in LMP in this region until the mid-21st century,and these increases may be approximately 23%-60%of the growth under the global warming scenario.Our results highlight the different rates of response of aerosol and WMGHG concentrations to the carbon neutrality goal,leading to various changes in LMP at global and regional scales.展开更多
Automated grading of dandruff severity is a clinically significant but challenging task due to the inherent ordinal nature of severity levels and the high prevalence of label noise from subjective expert annotations.S...Automated grading of dandruff severity is a clinically significant but challenging task due to the inherent ordinal nature of severity levels and the high prevalence of label noise from subjective expert annotations.Standard classification methods fail to address these dual challenges,limiting their real-world performance.In this paper,a novel,three-phase training framework is proposed that learns a robust ordinal classifier directly from noisy labels.The approach synergistically combines a rank-based ordinal regression backbone with a cooperative,semi-supervised learning strategy to dynamically partition the data into clean and noisy subsets.A hybrid training objective is then employed,applying a supervised ordinal loss to the clean set.The noisy set is simultaneously trained using a dualobjective that combines a semi-supervised ordinal loss with a parallel,label-agnostic contrastive loss.This design allows themodel to learn fromthe entire noisy subset while using contrastive learning to mitigate the risk of error propagation frompotentially corrupt supervision.Extensive experiments on a new,large-scale,multi-site clinical dataset validate our approach.Themethod achieves state-of-the-art performance with 80.71%accuracy and a 76.86%F1-score,significantly outperforming existing approaches,including a 2.26%improvement over the strongest baseline method.This work provides not only a robust solution for a practical medical imaging problem but also a generalizable framework for other tasks plagued by noisy ordinal labels.展开更多
Accurate temperature control and effective oxide removal are essential for achieving high-quality epitaxial growth in molecular beam epitaxy(MBE).However,traditional methods often rely on manual identification of refl...Accurate temperature control and effective oxide removal are essential for achieving high-quality epitaxial growth in molecular beam epitaxy(MBE).However,traditional methods often rely on manual identification of reflection high-energy electron diffraction(RHEED)patterns.This process is heavily influenced by the grower’s experience,leading to issues with reproducibility and limiting the potential for automation.In this report,we propose an unsupervised learning framework for realtime RHEED analysis during the deoxidation process.By incorporating temporal similarity constraints into contrastive learning,our model generates smooth and interpretable feature trajectories that illustrate transitions in the deoxidation state,thus eliminating the need for manual labeling.The model,pre-trained using grouped contrastive loss,shows significant improvement in RHEED feature boundary discrimination and localization of critical regions.We evaluated its generalizability through two transfer learning strategies:calibration-free clustering and few-shot fine-tuning.The pre-trained model achieved a clustering accuracy of 88.1%for GaAs deoxidation samples without additional labels and reached an accuracy of 94.3%to 95.5%after fine-tuning with just five sample pairs across GaAs,Ge,and InAs substrates.This framework is optimized for resource-constrained edge devices,allowing for real-time,plug-and-play integration with existing MBE systems and swift adaptation across various materials and equipment.This work paves the way for greater automation and improved reproducibility in semiconductor manufacturing.展开更多
Lacustrine groundwater discharge(LGD)plays an important role in water resources management.Previous studies have focused on LGD process in a single lake,but the differences in LGD process within the same region have n...Lacustrine groundwater discharge(LGD)plays an important role in water resources management.Previous studies have focused on LGD process in a single lake,but the differences in LGD process within the same region have not been thoroughly investigated.In this study,multiple tracers(hydrochemistry,𝛿D,𝛿18O and 222Rn)were used to compare mechanisms of LGD in Daihai and Ulansuhai Lake in Inner Mongoli1,Northwest China.The hydrochemical types showed a trend from groundwater to lake water,indicating a hydraulic connection between them.In addition,the𝛿D and𝛿18O values of sediment pore water were between the groundwater and lake water,indicating the LGD processes.The radon mass balance model was used to estimate the average groundwater discharge rates of Daihai and Ulansuhai Lake,which were 2.79 mm/day and 3.02 mm/day,respectively.The total nitrogen(TN),total phosphorus(TP),and fluoride inputs associated with LGD in Daihai Lake accounted for 97.52%,96.59%,and 95.84%of the total inputs,respectively.In contrast,TN,TP and fluoride inputs in Ulansuhai Lake were 53.56%,40.98%,and 36.25%,respectively.This indicates that the pollutant inputs associated with LGD posed a potential threat to the ecological stability of Daihai and Ulansuhai Lake.By comparison,the differences of LGD process and associated pollutant flux were controlled by hydrogeological conditions,lakebed permeability and human activities.This study provides a reference for water resources management in Daihai and Ulansuhai Lake basins while improving the understanding of LGD in the Yellow River basin.展开更多
Cancer has been recognized as one of the leading causes of mortality for decades.Magnetic resonance imaging(MRI)is a powerful imaging technology that has been widely applied in tumor diagnosis.Herein,we report the syn...Cancer has been recognized as one of the leading causes of mortality for decades.Magnetic resonance imaging(MRI)is a powerful imaging technology that has been widely applied in tumor diagnosis.Herein,we report the synthesis of magnetic iron oxide nanoparticles(MIONs)functionalized with multidentate thioether polymer ligand pentaerythritol tetrakis 3-mercaptopropionate-poly(methacrylic acid)(PTMPPMAA).Cytotoxicity assessment via the CCK-8 assay confirmed the low toxicity of the nanoparticles.MRI results showed excellent negative contrast enhancement.Bio-distribution study indicated gradual excretion of the nanoparticles.These MIONs@PTMP-PMAA exhibit strong negative contrast enhancement and present great potential as T_(2)-weighted contrast agents for MRI.展开更多
The morbidity rate of primary cardiac tumors(PCTs)is only 0.0138%.[1]Calcified amorphous tumors(CATs)are a particularly rare entity with only a few cases reported in the literature,and account for only 2.47%of PCTs.[2...The morbidity rate of primary cardiac tumors(PCTs)is only 0.0138%.[1]Calcified amorphous tumors(CATs)are a particularly rare entity with only a few cases reported in the literature,and account for only 2.47%of PCTs.[2]CATs can occur at any age and have been identified at various intracardiac locations.The clinical manifestations of patients are related to the location and size of the lesion.展开更多
文摘Once more to the lake is a representative work of the American Writer, Elwyn Brooks White, and has been acclaimed by people in the world. The paper offers a three-layered contrasting analysis of the essay. By detailed analysis of the contrasts running through the whole essay, the author finds that those contrasts are symbol of White's internal struggle and reflection for life.On the foundation of the three-layered contrasts, the paper presents the theme analysis and clarifies the content of the essay.
文摘Using the monthly geopotential heights and winds for 700 and 200 hPa for India during July and August, and the weekly M-100 Soviet rocketsonde temperature and wind data for Thumba (8.5 ° N, 76.9 ° E) during the last week of June and the first week of September for the two contrasting summer monsoon years 1975 (a very strong monsoon year) and 1979 (a very weak monsoon year), a study has been made to examine the mean circulation features of the troposphere over India, and the structures of the temperatures and the winds of the middle atmosphere over Thumba. The study suggested that the axis of the monsoon trough (AMT) at 700 hPa shifted southward in 1975 and northward towards the foothills of the Himalayas in 1979, from its normal position. Superimposed on the low-pressure area (AMT) at 700 hPa, a well-defined divergence was noticed at 200 hPa over the northern India in 1975.The mean temperatures at 25,50 and 60 km (middle atmosphere) over Thumba were cooler in 1975 than in 1979. While a cooling trend in 1975 and warming trend in 1979 were observed at 25 and 50 km, a reversed picture was noticed at 60 km. There was a weak easterly / westerly (weak westerly phase) zonal wind in 1975 and a strong easterly zonal wind in 1979. A phase reversal of the zonal wind was observed at 50 km. A tentative physical mechanism was offered, in terms of upward propagation of the two equatorially trapped planetary waves i.e. the Kelvin and the mixed Rossby-gravity waves, to explain the occurrence of the two spells of strong warmings in the mesosphere in 1975.
文摘The iconic image of a giant radiating dyke swarm subsequently fragmented into three pieces via supercontinental breakup was produced by Paul May in1971(see next page).That figure presented a large part of
基金This work was supported by Deakin Cyber Security Research Cluster National Natural Science Foundation of China under Grant Nos. 61304067 and 61202211 +1 种基金 Guangxi Key Laboratory of Trusted Software No. kx201325 the Fundamental Research Funds for the Central Universities under Grant No 31541311314.
文摘As the risk of malware is sharply increasing in Android platform,Android malware detection has become an important research topic.Existing works have demonstrated that required permissions of Android applications are valuable for malware analysis,but how to exploit those permission patterns for malware detection remains an open issue.In this paper,we introduce the contrasting permission patterns to characterize the essential differences between malwares and clean applications from the permission aspect Then a framework based on contrasting permission patterns is presented for Android malware detection.According to the proposed framework,an ensemble classifier,Enclamald,is further developed to detect whether an application is potentially malicious.Every contrasting permission pattern is acting as a weak classifier in Enclamald,and the weighted predictions of involved weak classifiers are aggregated to the final result.Experiments on real-world applications validate that the proposed Enclamald classifier outperforms commonly used classifiers for Android Malware Detection.
文摘The Awakening is about the heroine Edna Pontellier awakes and tries to reset her relation with the world in New Orleans,a place the family chose to spend the summer, where there also are influences working their way to awake Edna. Among them, theeffects from Madame Ratignolle and Madame Reisz are of great importance in the process of Edna's awakening and to her final sui-cide. This dissertation will see how Edna is affected by and distinguished from them, and get the conclusion that Edna fails being alife mediator by contrasting with the two women.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB0530000)the Discipline Construction Foundation of“Double World-class Project”.
文摘Laser wakefield accelerators(LWFAs)offer acceleration gradients up to 1000 times higher than those of conventional radio-frequency accelerators,offering a pathway to significantly more compact and cost-effective accelerator systems.This breakthrough opens up new possibilities for laboratory-scale light sources.All-optical inverse Compton scattering(AOCS)sources driven by LWFAs produce high-brightness,quasimonochromatic X rays with micrometer-scale source sizes,delivering the spatial coherence and resolution required for X-ray phase-contrast imaging(XPCI).These features position AOCS X-ray sources as promising tools for applications in biology,medicine,physics,and materials science.However,previous AOCS-based imaging studies have primarily focused on X-ray absorption imaging.In this work,we report successful experimental demonstrations of edge-enhanced in-line XPCI using energy-tunable,quasi-monochromatic AOCS X rays.With a spatial resolution of~20μm,our results clearly show the potential of high-resolution,AOCS-based XPCI applications.
基金support from the Research Council of Norway,Equinor,and Sekal with NFR project(Grant No.308826).
文摘Drill string vibration during drilling plays a vital and potentially decisive role in maintaining wellbore stability,as repeated impacts may lead to fatigue and borehole collapse.While drilling through geological layers,a material contrast may act as a localization point for wellbore damage.The hypothesis tested in this paper is that wellbore instability is focused on the boundary between the layers and that mechanical contrasts accelerate the wellbore collapse.In this study,an elastic-plastic damage model was employed to investigate the effects of repeated mechanical impacts on wellbore stability.A 2-dimensional(2D)model of a wellbore surrounded by contrasting materials was developed,and the accumulated damage caused by repeated lateral impacts was monitored.It was found that damage develops not only around the wall of the wellbore but also along the material boundaries.A sensitivity analysis was carried out to identify the impact of contrasts in both elastic(Young's modulus and Poisson's ratio)and plastic(cohesion,friction angle,and dilation angle)parameters between layers.Four damage patterns were identifiedin the simulated models.The results also suggested that the number of impacts required to reach the critical damage was highly affected by the contrast in elastic parameters,while cohesion and friction angle contrasts had a lesser effect.Additionally,increasing the contrast in the dilation angle localized the damage,thus reducing the number of impacts required to trigger wellbore failure.
文摘In high-intensity electromagnetic warfare,radar systems are persistently subjected to multi-jammer attacks,including potentially novel unknown jamming types that may emerge exclusively under wartime conditions.These jamming signals severely degrade radar detection performance.Precise recognition of these unknown and compound jamming signals is critical to enhancing the anti-jamming capabilities and overall reliability of radar systems.To address this challenge,this article proposes a novel open-set compound jamming cognition(OSCJC)method.The proposed method employs a detection-classification dual-network architecture,which not only overcomes the false alarm and misdetection issues of traditional closed-set recognition methods when dealing with unknown jamming but also effectively addresses the performance bottleneck of existing open-set recognition techniques focusing on single jamming scenarios in compound jamming environments.To achieve unknown jamming detection,we first employ a consistency labeling strategy to train the detection network using diverse known jamming samples.This strategy enables the network to acquire highly generalizable jamming features,thereby accurately localizing candidate regions for individual jamming components within compound jamming.Subsequently,we introduce contrastive learning to optimize the classification network,significantly enhancing both intra-class clustering and inter-class separability in the jamming feature space.This method not only improves the recognition accuracy of the classification network for known jamming types but also enhances its sensitivity to unknown jamming types.Simulations and experimental data are used to verify the effectiveness of the proposed OSCJC method.Compared with the state-of-the-art open-set recognition methods,the proposed method demonstrates superior recognition accuracy and enhanced environmental adaptability.
基金supported by the National Natural Science Foundation of China Funded Project(Project Name:Research on Robust Adaptive Allocation Mechanism of Human Machine Co-Driving System Based on NMS Features,Project Approval Number:52172381).
文摘To address the issue of scarce labeled samples and operational condition variations that degrade the accuracy of fault diagnosis models in variable-condition gearbox fault diagnosis,this paper proposes a semi-supervised masked contrastive learning and domain adaptation(SSMCL-DA)method for gearbox fault diagnosis under variable conditions.Initially,during the unsupervised pre-training phase,a dual signal augmentation strategy is devised,which simultaneously applies random masking in the time domain and random scaling in the frequency domain to unlabeled samples,thereby constructing more challenging positive sample pairs to guide the encoder in learning intrinsic features robust to condition variations.Subsequently,a ConvNeXt-Transformer hybrid architecture is employed,integrating the superior local detail modeling capacity of ConvNeXt with the robust global perception capability of Transformer to enhance feature extraction in complex scenarios.Thereafter,a contrastive learning model is constructed with the optimization objective of maximizing feature similarity across different masked instances of the same sample,enabling the extraction of consistent features from multiple masked perspectives and reducing reliance on labeled data.In the final supervised fine-tuning phase,a multi-scale attention mechanism is incorporated for feature rectification,and a domain adaptation module combining Local Maximum Mean Discrepancy(LMMD)with adversarial learning is proposed.This module embodies a dual mechanism:LMMD facilitates fine-grained class-conditional alignment,compelling features of identical fault classes to converge across varying conditions,while the domain discriminator utilizes adversarial training to guide the feature extractor toward learning domain-invariant features.Working in concert,they markedly diminish feature distribution discrepancies induced by changes in load,rotational speed,and other factors,thereby boosting the model’s adaptability to cross-condition scenarios.Experimental evaluations on the WT planetary gearbox dataset and the Case Western Reserve University(CWRU)bearing dataset demonstrate that the SSMCL-DA model effectively identifies multiple fault classes in gearboxes,with diagnostic performance substantially surpassing that of conventional methods.Under cross-condition scenarios,the model attains fault diagnosis accuracies of 99.21%for the WT planetary gearbox and 99.86%for the bearings,respectively.Furthermore,the model exhibits stable generalization capability in cross-device settings.
基金supported by the National Natural Science Foundation of China(82250410380 and 62171101)the Natural Science Foundation of Sichuan Province(24NSFSC6257)the China MOST2030 Brain Project(2022ZD0208500).
文摘Cerebral ischemia restricts cerebral blood flow(CBF),leading to unstable hemodynamics.Past studies of ischemia mainly focused on cortical CBF reduction.However,its impact on hemodynamic changes,especially temporal varying characteristics,remains poorly understood.Here,we collected cortical resting-state CBF in rats with left carotid artery blockage during occlusion–reperfusion,and measured the temporal variability and changes in laterality using a novel state-space method.This method was also applied to stroke EEG datasets to validate its effectiveness.After arterial occlusion,the left marginal motor,sensory,auditory,and visual cortices exhibited severe temporal variability impairments.The laterality analysis indicated that affected left regions showed inferior unilateral mean,inter-hemispheric transition probability,time fraction,and laterality duration,while the right side had a higher laterality time fraction and duration.These impairments recovered partially following blood flow restoration.Besides,the ischemic state-space metrics were positively correlated with the pre-occlusion baseline appearance.Stroke patients exhibited impaired temporal variability in the affected ischemic hemisphere.The state-space analysis revealed damaged CBF temporal variability during cerebral ischemia and predicted baseline-ischemia connections.
基金supported by the Regional Innovation System&Education(RISE)program through the Gangwon RISE Center,funded by the Ministry of Education(MOE)and the Gangwon State(G.S.),Republic of Korea(2025-RISE-10-006).
文摘This study aims to develop a novel,cost-effective method for fabricating silicone vascular phantoms(SVPs)using"chewy candy"as a dissolvable core material.The study explores the feasibility of using chewy candy to create detailed and intricate vascular models for clinical applications.The chewy candy,an amorphous material,was manually extruded to form vascular models of varying diameters.These models were embedded in a silicone mixture,which was then cured.The chewy candy was subsequently dissolved,leaving behind hollow silicone vascular channels.The SVPs were evaluated for their morphological accuracy and functionality through laser speckle contrast imaging.The SVPs successfully replicated vascular channels with consistent diameters,demonstrating minimal variation across different regions.Functional evaluation using laser speckle contrast imaging revealed distinct flow dynamics in Y-shaped and H-shaped SVPs,highlighting the potential for these phantoms to simulate realistic fluid dynamics in vascular systems.This study presents a simple,time-saving,and innovative approach to fabricating complex 3D SVPs using chewy candy.This method offers a viable alternative to traditional fabrication techniques,with potential applications in various biomedical fields.
基金supported by the National Key R&D Project of China(Nos.2022YFC2304205,2022YFC2304202)Key scientific research project of universities in Guangdong Province(No.2023KCXTD026)the Major Project of Guangzhou National Laboratory(No.GZNL2023A03002).
文摘Adjuvants enhance and prolong the immune response to therapeutic agents,such as drugs and vaccines.However,conventional adjuvants have limitations in terms of immune specificity and duration.Nanoadjuvants can leverage their nanoscale size to increase the capture efficacy of antigens by antigen-presenting cells and improve immunogen presentation for targeted delivery.Furthermore,noninvasive visualization of bifunctional nanoadjuvants with integrated efficacy and imaging postdelivery can provide insights into in vivo distribution and performance,aiding in the optimization and design of new dosage forms.This review systematically summarizes the structure,assembly,and function of nanoadjuvants alongside contrast agents.It delves into the impact of complex structures formed by nanoadjuvant-contrast agent interactions on antigen presentation,migration,imaging tracking,and visualization of immune cell recruitment.It also discusses how imaging can determine optimal immune intervals,vaccine safety,and toxicity while enabling diagnostic and therapeutic integration.Moreover,this paper discusses potential applications of novel adjuvants and promising imaging technologies that could have implications for future vaccine and drug development endeavors.
基金funded by the Deanship of Scientific Research(DSR)at King Abdulaziz University,Jeddah,under grant No.(IFPDP-261-22).
文摘Medical imaging is essential in modern health care,allowing accurate diagnosis and effective treatment planning.These images,however,often demonstrate low contrast,noise,and brightness distortion that reduce their diagnostic reliability.This review presents a structured and comprehensive analysis of advanced histogram equalization(HE)-based techniques for medical image enhancement.Our review methodology encompasses:(1)classical HE approaches and related limitations in medical domains;(2)adaptive schemes like Adaptive Histogram Equalization(AHE)and Contrast Limited Adaptive Histogrma Equalization(CLAHE)and their advance variants;(3)brightnesspreserving schemes like BBHE and MMBEBHE and related algorithms;(4)dynamic and recursive histogram equalization methods incorporating DHE and RMSHE;(5)fuzzy logic-based enhancement methodologies addressing uncertainty and noise in medical images;and(6)hybrid optimization methodologies through the application of metaheuristic algorithms(World Cup Optimization,Particle Swarm Optimization,Genetic Algorithms,along with histogram-based methodologies.)There is also a comparative discussion given based on contrast improvement,image brightness preservation,noise management,and computational efficiency.Such advancements have better capabilities of improving image quality,which is more important for improved diagnosis and image analysis.
基金funded by the National Natural Science Foundation of China(Grant No.42275039)the Meteorological Joint Fund by NSF and CMA(Grant No.U2342224)+1 种基金the National Key R&D Program of China(Grant No.2022YFC3701202)the S&T Development Fund of CAMS(Grant No.2024KJ019)。
文摘Global land monsoon precipitation(GLMP)is highly sensitive to changes in interhemispheric thermal contrast(ITC).Amplified interhemispheric asymmetries of GLMP due to enhanced ITC driven by high-level anthropogenic emissions are expected to simultaneously increase the probability of regional floods and droughts,threatening ecosystems within global terrestrial monsoon regions and the freshwater supply for billions of residents in these areas.In this study,the responses of GLMP to the evolution of ITC toward the carbon neutrality goal are assessed using multimodel outputs from a new model intercomparison project(CovidMIP).The results show that the Northern Hemisphere-Southern Hemisphere(NH-SH)asymmetry of GLMP in boreal summer weakens during the 2040s,as a persistent reduction in well-mixed greenhouse gas(WMGHG)emissions leads to a downward trend in the ITC after 2040.At the same time,the reduction in WMGHG emissions dampens the Eastern Hemisphere-Western Hemisphere(EH-WH)asymmetry of GLMP by inducing La Niña-like cooling and enhancing moisture transport to Inner America.The resulting increases in land monsoon precipitation(LMP)may alleviate drought under the global warming scenario by about 19%-25%and 7%-9%in the WH and SH monsoon regions,respectively.However,a persistent reduction in aerosol emissions in Asia will dominate the increases in LMP in this region until the mid-21st century,and these increases may be approximately 23%-60%of the growth under the global warming scenario.Our results highlight the different rates of response of aerosol and WMGHG concentrations to the carbon neutrality goal,leading to various changes in LMP at global and regional scales.
文摘Automated grading of dandruff severity is a clinically significant but challenging task due to the inherent ordinal nature of severity levels and the high prevalence of label noise from subjective expert annotations.Standard classification methods fail to address these dual challenges,limiting their real-world performance.In this paper,a novel,three-phase training framework is proposed that learns a robust ordinal classifier directly from noisy labels.The approach synergistically combines a rank-based ordinal regression backbone with a cooperative,semi-supervised learning strategy to dynamically partition the data into clean and noisy subsets.A hybrid training objective is then employed,applying a supervised ordinal loss to the clean set.The noisy set is simultaneously trained using a dualobjective that combines a semi-supervised ordinal loss with a parallel,label-agnostic contrastive loss.This design allows themodel to learn fromthe entire noisy subset while using contrastive learning to mitigate the risk of error propagation frompotentially corrupt supervision.Extensive experiments on a new,large-scale,multi-site clinical dataset validate our approach.Themethod achieves state-of-the-art performance with 80.71%accuracy and a 76.86%F1-score,significantly outperforming existing approaches,including a 2.26%improvement over the strongest baseline method.This work provides not only a robust solution for a practical medical imaging problem but also a generalizable framework for other tasks plagued by noisy ordinal labels.
基金supported by the Beijing Natural Science Foundation(Grant Nos.F251036 and L248103)CAS Project for Young Scientists in Basic Research(Grant Nos.YSBR-090 and YSBR-05)National Natural Science Foundation of China(Grant No.62274159).
文摘Accurate temperature control and effective oxide removal are essential for achieving high-quality epitaxial growth in molecular beam epitaxy(MBE).However,traditional methods often rely on manual identification of reflection high-energy electron diffraction(RHEED)patterns.This process is heavily influenced by the grower’s experience,leading to issues with reproducibility and limiting the potential for automation.In this report,we propose an unsupervised learning framework for realtime RHEED analysis during the deoxidation process.By incorporating temporal similarity constraints into contrastive learning,our model generates smooth and interpretable feature trajectories that illustrate transitions in the deoxidation state,thus eliminating the need for manual labeling.The model,pre-trained using grouped contrastive loss,shows significant improvement in RHEED feature boundary discrimination and localization of critical regions.We evaluated its generalizability through two transfer learning strategies:calibration-free clustering and few-shot fine-tuning.The pre-trained model achieved a clustering accuracy of 88.1%for GaAs deoxidation samples without additional labels and reached an accuracy of 94.3%to 95.5%after fine-tuning with just five sample pairs across GaAs,Ge,and InAs substrates.This framework is optimized for resource-constrained edge devices,allowing for real-time,plug-and-play integration with existing MBE systems and swift adaptation across various materials and equipment.This work paves the way for greater automation and improved reproducibility in semiconductor manufacturing.
基金supported by the Natural Science Foundation of Inner Mongolia Autonomous Region of China(No.2023QN04011)the National Natural Science Foundation of China(Nos.42307092 and 52279067)+1 种基金Ordos Science and Technology Major Project(No.ZD20232303)Project of Key Laboratory of River and Lake in Inner Mongolia Autonomous Region(No.2022QZBZ0003).
文摘Lacustrine groundwater discharge(LGD)plays an important role in water resources management.Previous studies have focused on LGD process in a single lake,but the differences in LGD process within the same region have not been thoroughly investigated.In this study,multiple tracers(hydrochemistry,𝛿D,𝛿18O and 222Rn)were used to compare mechanisms of LGD in Daihai and Ulansuhai Lake in Inner Mongoli1,Northwest China.The hydrochemical types showed a trend from groundwater to lake water,indicating a hydraulic connection between them.In addition,the𝛿D and𝛿18O values of sediment pore water were between the groundwater and lake water,indicating the LGD processes.The radon mass balance model was used to estimate the average groundwater discharge rates of Daihai and Ulansuhai Lake,which were 2.79 mm/day and 3.02 mm/day,respectively.The total nitrogen(TN),total phosphorus(TP),and fluoride inputs associated with LGD in Daihai Lake accounted for 97.52%,96.59%,and 95.84%of the total inputs,respectively.In contrast,TN,TP and fluoride inputs in Ulansuhai Lake were 53.56%,40.98%,and 36.25%,respectively.This indicates that the pollutant inputs associated with LGD posed a potential threat to the ecological stability of Daihai and Ulansuhai Lake.By comparison,the differences of LGD process and associated pollutant flux were controlled by hydrogeological conditions,lakebed permeability and human activities.This study provides a reference for water resources management in Daihai and Ulansuhai Lake basins while improving the understanding of LGD in the Yellow River basin.
基金financially supported by the International Cooperation Program of the Ministry of Science and Technology of Hubei Province(No.2023EHA069)Shenzhen Science and Technology Program(No.JCYJ20230807143702005)+1 种基金National Foreign Experts Program(No.G2022027015L)the National Natural Science Foundation of China(No.82302265).
文摘Cancer has been recognized as one of the leading causes of mortality for decades.Magnetic resonance imaging(MRI)is a powerful imaging technology that has been widely applied in tumor diagnosis.Herein,we report the synthesis of magnetic iron oxide nanoparticles(MIONs)functionalized with multidentate thioether polymer ligand pentaerythritol tetrakis 3-mercaptopropionate-poly(methacrylic acid)(PTMPPMAA).Cytotoxicity assessment via the CCK-8 assay confirmed the low toxicity of the nanoparticles.MRI results showed excellent negative contrast enhancement.Bio-distribution study indicated gradual excretion of the nanoparticles.These MIONs@PTMP-PMAA exhibit strong negative contrast enhancement and present great potential as T_(2)-weighted contrast agents for MRI.
文摘The morbidity rate of primary cardiac tumors(PCTs)is only 0.0138%.[1]Calcified amorphous tumors(CATs)are a particularly rare entity with only a few cases reported in the literature,and account for only 2.47%of PCTs.[2]CATs can occur at any age and have been identified at various intracardiac locations.The clinical manifestations of patients are related to the location and size of the lesion.
