Unmanned aerial vehicle(UAV)-borne gamma-ray spectrum survey plays a crucial role in geological mapping,radioactive mineral exploration,and environmental monitoring.However,raw data are often compromised by flight and...Unmanned aerial vehicle(UAV)-borne gamma-ray spectrum survey plays a crucial role in geological mapping,radioactive mineral exploration,and environmental monitoring.However,raw data are often compromised by flight and instrument background noise,as well as detector resolution limitations,which affect the accuracy of geological interpretations.This study aims to explore the application of the Real-ESRGAN algorithm in the super-resolution reconstruction of UAV-borne gamma-ray spectrum images to enhance spatial resolution and the quality of geological feature visualization.We conducted super-resolution reconstruction experiments with 2×,4×and 6×magnification using the Real-ESRGAN algorithm,comparing the results with three other mainstream algorithms(SRCNN,SRGAN,FSRCNN)to verify the superiority in image quality.The experimental results indicate that Real-ESRGAN achieved a structural similarity index(SSIM)value of 0.950 at 2×magnification,significantly higher than the other algorithms,demonstrating its advantage in detail preservation.Furthermore,Real-ESRGAN effectively reduced ringing and overshoot artifacts,enhancing the clarity of geological structures and mineral deposit sites,thus providing high-quality visual information for geological exploration.展开更多
Remote sensing image super-resolution technology is pivotal for enhancing image quality in critical applications including environmental monitoring,urban planning,and disaster assessment.However,traditional methods ex...Remote sensing image super-resolution technology is pivotal for enhancing image quality in critical applications including environmental monitoring,urban planning,and disaster assessment.However,traditional methods exhibit deficiencies in detail recovery and noise suppression,particularly when processing complex landscapes(e.g.,forests,farmlands),leading to artifacts and spectral distortions that limit practical utility.To address this,we propose an enhanced Super-Resolution Generative Adversarial Network(SRGAN)framework featuring three key innovations:(1)Replacement of L1/L2 loss with a robust Charbonnier loss to suppress noise while preserving edge details via adaptive gradient balancing;(2)A multi-loss joint optimization strategy dynamically weighting Charbonnier loss(β=0.5),Visual Geometry Group(VGG)perceptual loss(α=1),and adversarial loss(γ=0.1)to synergize pixel-level accuracy and perceptual quality;(3)A multi-scale residual network(MSRN)capturing cross-scale texture features(e.g.,forest canopies,mountain contours).Validated on Sentinel-2(10 m)and SPOT-6/7(2.5 m)datasets covering 904 km2 in Motuo County,Xizang,our method outperforms the SRGAN baseline(SR4RS)with Peak Signal-to-Noise Ratio(PSNR)gains of 0.29 dB and Structural Similarity Index(SSIM)improvements of 3.08%on forest imagery.Visual comparisons confirm enhanced texture continuity despite marginal Learned Perceptual Image Patch Similarity(LPIPS)increases.The method significantly improves noise robustness and edge retention in complex geomorphology,demonstrating 18%faster response in forest fire early warning and providing high-resolution support for agricultural/urban monitoring.Future work will integrate spectral constraints and lightweight architectures.展开更多
Background:Continuous care for children with enterostomy and their families has been gaining popularity in China.Objective:To evaluate the feasibility of continuous care for children with enterostomy and their familie...Background:Continuous care for children with enterostomy and their families has been gaining popularity in China.Objective:To evaluate the feasibility of continuous care for children with enterostomy and their families in China.Methods:The PubMed,Web of Science,Embase,Cochrane Library,EBSCO,CNKI,CBM,VIP,and WanFang were searched for clinical trials until December 30,2025.Two reviewers independently searched articles,evaluated quality and extracted data.This review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses(PRISMA).Results:33 studies involving 2774 participants were included.The meta-analysis showed that continuous care strategy can significantly reduce the incidence of complications in children with enterostomy(OR=0.20,95%CI=0.16-0.26,p<0.001,I2=0%),effectively improve the family caregiver ability for enterostomy(MD=-10.34,95%CI=-13.82 to-6.85,p<0.001,I2=99%),shorten the time for family members to replace stoma bags(MD=-13.57,95%CI=-19.66 to-7.49,p<0.001,I2=100%),and alleviate negative emotions such as anxiety(SMD=-1.80,95%CI=-2.36 to-1.23,p<0.001,I2=92%)and depression(SMD=-1.54,95%CI=-2.04 to-1.04,p<0.001,I2=89%)in the families of the affected children.Conclusions:Continuous care can reduce complications of enterostomy in children,improve the family caregiver ability for enterostomy and alleviate negative emotions of family members such as anxiety and depression.展开更多
We report an immobilized enzyme-catalyzed batch and continuous-flow synthesis of optically pure ethyl(R)-pantothenate((R)-PaOEt),the direct precursor of d-pantothenic acid.Firstly,a ketoreductase mutant designated as ...We report an immobilized enzyme-catalyzed batch and continuous-flow synthesis of optically pure ethyl(R)-pantothenate((R)-PaOEt),the direct precursor of d-pantothenic acid.Firstly,a ketoreductase mutant designated as M2,carrying two-point mutations of F97L and M242F relative to the wild-type SSCR,was constructed by site-directed mutagenesis,exhibited simultaneously improved activity toward ethyl 2′-ketopantothenate(K-PaOEt)and isopropanol,and could effectively catalyze the stereoselective reduction of K-PaOEt to(R)-PaOEt by using isopropanol as the sacrificial co-substrate to regenerate NADPH.After screening six commercially available carriers,an amino resin LXTE-700 was identified as the best solid support for the immobilization of M2 via the glutaraldehyde activation method.Upon optimization of the immobilization process and reaction conditions,the fabricated immobilized enzyme M2@amino resin demonstrated excellent recyclability and reusability,with the complete conversion of K-PaOEt to(R)-PaOEt being still realized after 12 cycles of reuse.Finally,M2@amino resin-catalyzed synthesis of(R)-PaOEt was successfully implemented in continuous-flow,accomplishing a 6.3 times higher space-time yield than that with the batch synthesis(529.2 versus 84 g L^(-1) d^(-1)).Our developed flow biocatalysis system also features an outstanding operational stability,as evidenced by the 100%conversion rate achieved after 15 consecutive days of operation.展开更多
A full-sectional microstructure characterization method was developed to investigate the formation of coarse slag rims during the continuous casting of hypo-peritectic steel.The cross-sectional microstructural analysi...A full-sectional microstructure characterization method was developed to investigate the formation of coarse slag rims during the continuous casting of hypo-peritectic steel.The cross-sectional microstructural analysis of typical slag rims for two highly crystalline powders revealed that their formation was primarily driven by the solidification of the liquid slag.Distinct differences were observed in the microstructures of slag rims from the two powders.Powder A(characterized by a higher breaking temperature and viscosity)displayed alternating lamellar microstructures of coarse and fine phases,with the coarse phases composed of akermanite-gehlenite transition phases.In contrast,powder B(with a lower breaking temperature and viscosity)predominantly comprised regular akermanite-gehlenite crystals interspersed with a certain amount of glassy phases.Numerical simulations of a three-phase fluid flow coupled with heat transfer indicate that slag rim formation correlates with mold oscillation.Solidification of the liquid slag at the slag rim front predominantly occurs during the negative stroke of the mold oscillation.The average heating rate during the ascending stage of the mold reaches approximately 100 K·s^(−1),whereas the average cooling rate during the descending stage attains 400 K·s^(−1).This temperature variation leads to the formation of lamellar microstructures,whereas the ascending stage promotes the formation of coarse structures and thicker slag rims.Based on the powder properties,two distinct formation pathways exist for highly crystalline mold powders.For the powders with a higher breaking temperature,higher viscosity,and narrower solidification range(powder A),coarse microstructures and thicker slag rims were preferentially formed.For powders with lower breaking temperature and viscosity and wider solidification ranges(powder B),the liquid slag resisted rapid solidification,and the extended mushy zone allowed the partial liquid slag to persist at the slag rim front,promoting the formation of a thin slag rim.This study enhances the understanding of slag rim formation in highly crystalline mold powders and provides critical insights into the control of longitudinal surface cracks in hypo-peritectic steel.展开更多
This paper deals with the numerical solutions of two-dimensional(2D)semi-linear reaction-diffusion equations(SLRDEs)with piecewise continuous argument(PCA)in reaction term.A high-order compact difference method called...This paper deals with the numerical solutions of two-dimensional(2D)semi-linear reaction-diffusion equations(SLRDEs)with piecewise continuous argument(PCA)in reaction term.A high-order compact difference method called Ⅰ-type basic scheme is developed for solving the equations and it is proved under the suitable conditions that this method has the computational accuracy O(τ^(2)+h_(x)^(4)+h_(y)^(4)),where τ,h_(x )and h_(y) are the calculation stepsizes of the method in t-,x-and y-direction,respectively.With the above method and Newton linearized technique,a Ⅱ-type basic scheme is also suggested.Based on the both basic schemes,the corresponding Ⅰ-and Ⅱ-type alternating direction implicit(ADI)schemes are derived.Finally,with a series of numerical experiments,the computational accuracy and efficiency of the four numerical schemes are further illustrated.展开更多
The rapid development of super-resolution microscopy has made it possible to observe subcellular structures and dynamic behaviors in living cells with nanoscale spatial resolution, greatly advancing progress in life s...The rapid development of super-resolution microscopy has made it possible to observe subcellular structures and dynamic behaviors in living cells with nanoscale spatial resolution, greatly advancing progress in life sciences. As hardware technology continues to evolve, the availability of new fluorescent probes with superior performance is becoming increasingly important. In recent years, fluorescent nanoprobes (FNPs) have emerged as highly promising fluorescent probes for bioimaging due to their high brightness and excellent photostability. This paper focuses on the development and applications of FNPs as probes for live-cell super-resolution imaging. It provides an overview of different super-resolution methods, discusses the performance requirements for FNPs in these methods, and reviews the latest applications of FNPs in the super-resolution imaging of living cells. Finally, it addresses the challenges and future outlook in this field.展开更多
BACKGROUND Continuous glucose monitoring(CGM)metrics,such as time in range(TIR)and glycemic risk index(GRI),have been linked to various diabetes-related complications,including diabetic foot(DF).AIM To investigate the...BACKGROUND Continuous glucose monitoring(CGM)metrics,such as time in range(TIR)and glycemic risk index(GRI),have been linked to various diabetes-related complications,including diabetic foot(DF).AIM To investigate the association between CGM-derived indicators and the risk of DF in individuals with type 2 diabetes mellitus(T2DM).METHODS A total of 591 individuals with T2DM(297 with DF and 294 without DF)were enrolled.Relevant clinical data,complications,comorbidities,hematological parameters,and 72-hour CGM data were collected.Logistic regression analysis was employed to examine the relationship between these measurements and the risk of DF.RESULTS Individuals with DF exhibited higher mean blood glucose(MBG)levels and increased proportions of time above range(TAR),TAR level 1,and TAR level 2,but lower TIR(all P<0.001).Patients with DF had significantly lower rates of achieving target ranges for TIR,TAR,and TAR level 2 than those without DF(all P<0.05).Logistic regression analysis revealed that GRI,MBG,and TAR level 1 were positively associated with DF risk,while TIR was inversely correlated(all P<0.05).Achieving TIR and TAR was inversely correlated with white blood cell count and glycated hemoglobin A1c levels(P<0.05).Additionally,achieving TAR was influenced by fasting plasma glucose,body mass index,diabetes duration,and antidiabetic medication use.CONCLUSION CGM metrics,particularly TIR and GRI,are significantly associated with the risk of DF in T2DM,emphasizing the importance of improved glucose control.展开更多
The application of liquid core reduction(LCR)technology in thin slab continuous casting can refine the internal microstruc-tures of slabs and improve their production efficiency.To avoid crack risks caused by large de...The application of liquid core reduction(LCR)technology in thin slab continuous casting can refine the internal microstruc-tures of slabs and improve their production efficiency.To avoid crack risks caused by large deformation during the LCR process and to minimize the thickness of the slab in bending segments,the maximum theoretical reduction amount and the corresponding reduction scheme for the LCR process must be determined.With SPA-H weathering steel as a specific research steel grade,the distributions of tem-perature and deformation fields of a slab with the LCR process were analyzed using a three-dimensional thermal-mechanical finite ele-ment model.High-temperature tensile tests were designed to determine the critical strain of corner crack propagation and intermediate crack initiation with various strain rates and temperatures,and a prediction model of the critical strain for two typical cracks,combining the effects of strain rate and temperature,was proposed by incorporating the Zener-Hollomon parameter.The crack risks with different LCR schemes were calculated using the crack risk prediction model,and the maximum theoretical reduction amount for the SPA-H slab with a transverse section of 145 mm×1600 mm was 41.8 mm,with corresponding reduction amounts for Segment 0 to Segment 4 of 15.8,7.3,6.5,6.4,and 5.8 mm,respectively.展开更多
During extensive gully land consolidation projects on China's Loess Plateau,many loess-bedrock fill slopes were formed,which frequently experience shallow landslides induced by rainfall.However,studies on loess-be...During extensive gully land consolidation projects on China's Loess Plateau,many loess-bedrock fill slopes were formed,which frequently experience shallow landslides induced by rainfall.However,studies on loess-bedrock slope failure triggered by continuous heavy rainfall are limited,and the role of the soilerock interface between the original bedrock slope and fill slope in the hydrological and failure process of the slope remains unclear.In this study,we conducted a continuous rainfall model test on a loess-bedrock fill slope.During the test,the responses of volume water content,pore pressure,micro deformation,and movement of the infiltration front were observed.The hydrological process and failure mechanism were then analysed.The findings suggest that the soilerock interface is a predominant infiltration surface within the slope.Rainfall infiltration rates at the interface reach 1.24-2.80 times those of the fill slope,with peak interfacial pore water pressure exceeding that of the loess fill.Furthermore,the infiltration front moves rapidly along the interface toward the bottom of the slope,reducing interfacial cohesion between bedrock and loess.The slope failure modes are summarised into three phases:local failure→flow slide and crack penetration→multistage block retrogressive slides.The cracks generated at the slope surface serve as key determinants of the geometry and scale of shallow landslides.Therefore,we recommend targeted engineering interventions to mitigate the instability and erosion of loessebedrock fill slopes.展开更多
Based on thermodynamic calculations and continuous rheological extrusion(CRE)technology,Al-Ti-V-B master alloys were designed and prepared.The morphology and the distribution of the refined phases in the master alloys...Based on thermodynamic calculations and continuous rheological extrusion(CRE)technology,Al-Ti-V-B master alloys were designed and prepared.The morphology and the distribution of the refined phases in the master alloys were analyzed by XRD,SEM,and TEM.The effects of master alloy addition and holding time on the microstructure and mechanical properties of A356 alloy were investigated.Under the optimum refiner addition of 0.3wt.%and the holding time of 20 min,the average grain size of the refined A356 alloy is 151.8±9.11μm,89.62%lower than that of original A356 alloy.The tensile strength and elongation of as-cast A356refined alloy are 196.11 MPa and 5.75%,respectively.After T6 treatment,the tensile strength and elongation of A356 refined alloy are 290.1 MPa and 3.09%,respectively.The fracture morphology is characterized by a predominance of along-crystal fracture with a small amount of through-crystal fracture,attributed to the refined grains.Finer grains promote crack path deflection and localized plastic deformation,enhancing energy dissipation and reducing the tendency for brittle fracture.This study provides a novel approach to improving the mechanical properties of A356 alloy through grain refinement using CRE Al-Ti-V-B master alloy.展开更多
Image super-resolution reconstruction technology is currently widely used in medical imaging,video surveillance,and industrial quality inspection.It not only enhances image quality but also improves details and visual...Image super-resolution reconstruction technology is currently widely used in medical imaging,video surveillance,and industrial quality inspection.It not only enhances image quality but also improves details and visual perception,significantly increasing the utility of low-resolution images.In this study,an improved image superresolution reconstruction model based on Generative Adversarial Networks(SRGAN)was proposed.This model introduced a channel and spatial attention mechanism(CSAB)in the generator,allowing it to effectively leverage the information from the input image to enhance feature representations and capture important details.The discriminator was designed with an improved PatchGAN architecture,which more accurately captured local details and texture information of the image.With these enhanced generator and discriminator architectures and an optimized loss function design,this method demonstrated superior performance in image quality assessment metrics.Experimental results showed that this model outperforms traditional methods,presenting more detailed and realistic image details in the visual effects.展开更多
Significant advancements have been achieved in the field of Single Image Super-Resolution(SISR)through the utilization of Convolutional Neural Networks(CNNs)to attain state-of-the-art performance.Recent efforts have e...Significant advancements have been achieved in the field of Single Image Super-Resolution(SISR)through the utilization of Convolutional Neural Networks(CNNs)to attain state-of-the-art performance.Recent efforts have explored the incorporation of Transformers to augment network performance in SISR.However,the high computational cost of Transformers makes them less suitable for deployment on lightweight devices.Moreover,the majority of enhancements for CNNs rely predominantly on small spatial convolutions,thereby neglecting the potential advantages of large kernel convolution.In this paper,the authors propose a Multi-Perception Large Kernel convNet(MPLKN)which delves into the exploration of large kernel convolution.Specifically,the authors have architected a Multi-Perception Large Kernel(MPLK)module aimed at extracting multi-scale features and employ a stepwise feature fusion strategy to seamlessly integrate these features.In addition,to enhance the network's capacity for nonlinear spatial information processing,the authors have designed a Spatial-Channel Gated Feed-forward Network(SCGFN)that is capable of adapting to feature interactions across both spatial and channel dimensions.Experimental results demonstrate that MPLKN outperforms other lightweight image super-resolution models while maintaining a minimal number of parameters and FLOPs.展开更多
Ensuring the consistent mechanical performance of three-dimensional(3D)-printed continuous fiber-reinforced composites is a significant challenge in additive manufacturing.The current reliance on manual monitoring exa...Ensuring the consistent mechanical performance of three-dimensional(3D)-printed continuous fiber-reinforced composites is a significant challenge in additive manufacturing.The current reliance on manual monitoring exacerbates this challenge by rendering the process vulnerable to environmental changes and unexpected factors,resulting in defects and inconsistent product quality,particularly in unmanned long-term operations or printing in extreme environments.To address these issues,we developed a process monitoring and closed-loop feedback control strategy for the 3D printing process.Real-time printing image data were captured and analyzed using a well-trained neural network model,and a real-time control module-enabled closed-loop feedback control of the flow rate was developed.The neural network model,which was based on image processing and artificial intelligence,enabled the recognition of flow rate values with an accuracy of 94.70%.The experimental results showed significant improvements in both the surface performance and mechanical properties of printed composites,with three to six times improvement in tensile strength and elastic modulus,demonstrating the effectiveness of the strategy.This study provides a generalized process monitoring and feedback control method for the 3D printing of continuous fiber-reinforced composites,and offers a potential solution for remote online monitoring and closed-loop adjustment in unmanned or extreme space environments.展开更多
Recent Super-Resolution(SR)algorithms often suffer from excessive model complexity,high computational costs,and limited flexibility across varying image scales.To address these challenges,we propose DDNet,a dynamic an...Recent Super-Resolution(SR)algorithms often suffer from excessive model complexity,high computational costs,and limited flexibility across varying image scales.To address these challenges,we propose DDNet,a dynamic and lightweight SR framework designed for arbitrary scaling factors.DDNet integrates a residual learning structure with an Adaptively fusion Feature Block(AFB)and a scale-aware upsampling module,effectively reducing parameter overhead while preserving reconstruction quality.Additionally,we introduce DDNetGAN,an enhanced variant that leverages a relativistic Generative Adversarial Network(GAN)to further improve texture realism.To validate the proposed models,we conduct extensive training using the DIV2K and Flickr2K datasets and evaluate performance across standard benchmarks including Set5,Set14,Urban100,Manga109,and BSD100.Our experiments cover both symmetric and asymmetric upscaling factors and incorporate ablation studies to assess key components.Results show that DDNet and DDNetGAN achieve competitive performance compared with mainstream SR algorithms,demonstrating a strong balance between accuracy,efficiency,and flexibility.These findings highlight the potential of our approach for practical real-world super-resolution applications.展开更多
Blood cells are the most integral part of the body,which are made up of erythrocytes,platelets and white blood cells.The examination of subcellular structures and proteins within blood cells at the nanoscale can provi...Blood cells are the most integral part of the body,which are made up of erythrocytes,platelets and white blood cells.The examination of subcellular structures and proteins within blood cells at the nanoscale can provide valuable insights into the health status of an individual,accurate diagnosis,and efficient treatment strategies for diseases.Super-resolution microscopy(SRM)has recently emerged as a cutting-edge tool for the study of blood cells,providing numerous advantages over traditional methods for examining subcellular structures and proteins.In this paper,we focus on outlining the fundamental principles of various SRM techniques and their applications in both normal and diseased states of blood cells.Furthermore,future prospects of SRM techniques in the analysis of blood cells are also discussed.展开更多
A new scheme of super-resolution optical fluctuation imaging(SOFI)is proposed to broaden its application in the high-order cumulant reconstruction by optimizing blinking characteristics,eliminating noise in raw data a...A new scheme of super-resolution optical fluctuation imaging(SOFI)is proposed to broaden its application in the high-order cumulant reconstruction by optimizing blinking characteristics,eliminating noise in raw data and applying multi-resolution analysis in cumulant reconstruction.A motor-driven rotating mask optical modulation system is designed to adjust the excitation lightfield and allows for fast deployment.Active-modulated fluorescence fluctuation superresolution microscopy with multi-resolution analysis(AMF-MRA-SOFI)demonstrates enhanced resolution ability and reconstruction quality in experiments performed on sample of conventional dyes,achieving a resolution of 100 nm in the fourth order compared to conventional SOFI reconstruction.Furthermore,our approach combining expansion super-resolution achieved a resolution at-57 nm.展开更多
The evaluation of adsorption states and shale gas content in shale fractures and pores relies on the analysis of these fractures and pores.Scanning electron microscopy images are commonly used for shale analysis;howev...The evaluation of adsorption states and shale gas content in shale fractures and pores relies on the analysis of these fractures and pores.Scanning electron microscopy images are commonly used for shale analysis;however,their low resolution,particularly the loss of high-frequency information at pore edges,presents challenges in analyzing fractures and pores in shale gas reservoirs.This study introduced a novel neural network called the spatial-spectral domain attention network(SSDAN),which employed spatial and spectral domain attention mechanisms to extract features and restore information in parallel.The network generated super-resolution images through a fusion module that included CNN-based spatial blocks for pixel-level image information recovery,spectral blocks to process Fourier transform information of images and enhance high-frequency recovery,and an adaptive vision transformer to process Fourier transform block information,eliminating the need for a preset image size.The SSDAN model demonstrated exceptional performance in comparative experiments on marine shale and marine continental shale datasets,achieving optimal performance on key indicators such as peak signal-to-noise ratio,structural similarity,learned perceptual image patch similarity,and Frechet inception distance while also exhibiting superior visual performance in pore recovery.Ablation experiments further confirmed the effectiveness of the spatial blocks,channel attention,spectral blocks,and frequency loss function in the model.The SSDAN model showed remarkable capability in enhancing the resolution of shale gas reservoir images and restoring high-frequency information at pore edges,thereby validating its effectiveness in unconventional natural gas reservoir analyses.展开更多
Plant diseases are a major threat that can severely impact the production of agriculture and forestry.This can lead to the disruption of ecosystem functions and health.With its ability to capture continuous narrow-ban...Plant diseases are a major threat that can severely impact the production of agriculture and forestry.This can lead to the disruption of ecosystem functions and health.With its ability to capture continuous narrow-band spectra,hyperspectral technology has become a crucial tool to monitor crop diseases using remote sensing.However,existing continuous wavelet analysis(CWA)methods suffer from feature redundancy issues,while the continuous wavelet projection algorithm(CWPA),an optimization approach for feature selection,has not been fully validated to monitor plant diseases.This study utilized rice bacterial leaf blight(BLB)as an example by evaluating the performance of four wavelet basis functions-Gaussian2,Mexican hat,Meyer,andMorlet-within theCWAandCWPAframeworks.Additionally,the classification models were constructed using the k-nearest neighbors(KNN),randomforest(RF),and Naïve Bayes(NB)algorithms.The results showed the following:(1)Compared to traditional CWA,CWPA significantly reduced the number of required features.Under the CWPA framework,almost all the model combinations achieved maximum classification accuracy with only one feature.In contrast,the CWA framework required three to seven features.(2)Thechoice of wavelet basis functions markedly affected the performance of themodel.Of the four functions tested,the Meyer wavelet demonstrated the best overall performance in both the CWPA and CWA frameworks.(3)Under theCWPAframework,theMeyer-KNNandMeyer-NBcombinations achieved the highest overall accuracy of 93.75%using just one feature.In contrast,under the CWA framework,the CWA-RF combination achieved comparable accuracy(93.75%)but required six features.This study verified the technical advantages of CWPA for monitoring crop diseases,identified an optimal wavelet basis function selection scheme,and provided reliable technical support to precisely monitor BLB in rice(Oryza sativa).Moreover,the proposed methodological framework offers a scalable approach for the early diagnosis and assessment of plant stress,which can contribute to improved accuracy and timeliness when plant stress is monitored.展开更多
Infrared imaging technology has been widely adopted in various fields,such as military reconnaissance,medical diagnosis,and security monitoring,due to its excellent ability to penetrate smoke and fog.However,the preva...Infrared imaging technology has been widely adopted in various fields,such as military reconnaissance,medical diagnosis,and security monitoring,due to its excellent ability to penetrate smoke and fog.However,the prevalent low resolution of infrared images severely limits the accurate interpretation of their contents.In addition,deploying super-resolution models on resource-constrained devices faces significant challenges.To address these issues,this study proposes a lightweight super-resolution network for infrared images based on an adaptive attention mechanism.The network’s dynamic weighting module automatically adjusts the weights of the attention and nonattention branch outputs based on the network’s characteristics at different levels.Among them,the attention branch is further subdivided into pixel attention and brightness-texture attention,which are specialized for extracting the most informative features in infrared images.Meanwhile,the non-attention branch supplements the extraction of those neglected features to enhance the comprehensiveness of the features.Through ablation experiments,we verify the effectiveness of the proposed module.Finally,through experiments on two datasets,FLIR and Thermal101,qualitative and quantitative results demonstrate that the model can effectively recover high-frequency details of infrared images and significantly improve image resolution.In detail,compared with the suboptimal method,we have reduced the number of parameters by 30%and improved the model performance.When the scale factor is 2,the peak signal-tonoise ratio of the test datasets FLIR and Thermal101 is improved by 0.09 and 0.15 dB,respectively.When the scale factor is 4,it is improved by 0.05 and 0.09 dB,respectively.In addition,due to the lightweight design of the network structure,it has a low computational cost.It is suitable for deployment on edge devices,thus effectively enhancing the sensing performance of infrared imaging devices.展开更多
基金supported by the National Natural Science Foundation of China(Nos.12205044 and 12265003)2024 Jiangxi Province Civil-Military Integration Research Institute‘BeiDou+’Project Subtopic(No.2024JXRH0Y06).
文摘Unmanned aerial vehicle(UAV)-borne gamma-ray spectrum survey plays a crucial role in geological mapping,radioactive mineral exploration,and environmental monitoring.However,raw data are often compromised by flight and instrument background noise,as well as detector resolution limitations,which affect the accuracy of geological interpretations.This study aims to explore the application of the Real-ESRGAN algorithm in the super-resolution reconstruction of UAV-borne gamma-ray spectrum images to enhance spatial resolution and the quality of geological feature visualization.We conducted super-resolution reconstruction experiments with 2×,4×and 6×magnification using the Real-ESRGAN algorithm,comparing the results with three other mainstream algorithms(SRCNN,SRGAN,FSRCNN)to verify the superiority in image quality.The experimental results indicate that Real-ESRGAN achieved a structural similarity index(SSIM)value of 0.950 at 2×magnification,significantly higher than the other algorithms,demonstrating its advantage in detail preservation.Furthermore,Real-ESRGAN effectively reduced ringing and overshoot artifacts,enhancing the clarity of geological structures and mineral deposit sites,thus providing high-quality visual information for geological exploration.
基金This study was supported by:Inner Mongolia Academy of Forestry Sciences Open Research Project(Grant No.KF2024MS03)The Project to Improve the Scientific Research Capacity of the Inner Mongolia Academy of Forestry Sciences(Grant No.2024NLTS04)The Innovation and Entrepreneurship Training Program for Undergraduates of Beijing Forestry University(Grant No.X202410022268).
文摘Remote sensing image super-resolution technology is pivotal for enhancing image quality in critical applications including environmental monitoring,urban planning,and disaster assessment.However,traditional methods exhibit deficiencies in detail recovery and noise suppression,particularly when processing complex landscapes(e.g.,forests,farmlands),leading to artifacts and spectral distortions that limit practical utility.To address this,we propose an enhanced Super-Resolution Generative Adversarial Network(SRGAN)framework featuring three key innovations:(1)Replacement of L1/L2 loss with a robust Charbonnier loss to suppress noise while preserving edge details via adaptive gradient balancing;(2)A multi-loss joint optimization strategy dynamically weighting Charbonnier loss(β=0.5),Visual Geometry Group(VGG)perceptual loss(α=1),and adversarial loss(γ=0.1)to synergize pixel-level accuracy and perceptual quality;(3)A multi-scale residual network(MSRN)capturing cross-scale texture features(e.g.,forest canopies,mountain contours).Validated on Sentinel-2(10 m)and SPOT-6/7(2.5 m)datasets covering 904 km2 in Motuo County,Xizang,our method outperforms the SRGAN baseline(SR4RS)with Peak Signal-to-Noise Ratio(PSNR)gains of 0.29 dB and Structural Similarity Index(SSIM)improvements of 3.08%on forest imagery.Visual comparisons confirm enhanced texture continuity despite marginal Learned Perceptual Image Patch Similarity(LPIPS)increases.The method significantly improves noise robustness and edge retention in complex geomorphology,demonstrating 18%faster response in forest fire early warning and providing high-resolution support for agricultural/urban monitoring.Future work will integrate spectral constraints and lightweight architectures.
文摘Background:Continuous care for children with enterostomy and their families has been gaining popularity in China.Objective:To evaluate the feasibility of continuous care for children with enterostomy and their families in China.Methods:The PubMed,Web of Science,Embase,Cochrane Library,EBSCO,CNKI,CBM,VIP,and WanFang were searched for clinical trials until December 30,2025.Two reviewers independently searched articles,evaluated quality and extracted data.This review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses(PRISMA).Results:33 studies involving 2774 participants were included.The meta-analysis showed that continuous care strategy can significantly reduce the incidence of complications in children with enterostomy(OR=0.20,95%CI=0.16-0.26,p<0.001,I2=0%),effectively improve the family caregiver ability for enterostomy(MD=-10.34,95%CI=-13.82 to-6.85,p<0.001,I2=99%),shorten the time for family members to replace stoma bags(MD=-13.57,95%CI=-19.66 to-7.49,p<0.001,I2=100%),and alleviate negative emotions such as anxiety(SMD=-1.80,95%CI=-2.36 to-1.23,p<0.001,I2=92%)and depression(SMD=-1.54,95%CI=-2.04 to-1.04,p<0.001,I2=89%)in the families of the affected children.Conclusions:Continuous care can reduce complications of enterostomy in children,improve the family caregiver ability for enterostomy and alleviate negative emotions of family members such as anxiety and depression.
基金the Science and Technology R&D Major Project of Jiangxi Province(No.20244AFI92001)the National Natural Science Foundation of China(Nos.22071033 and 21801047)for the financial supports.
文摘We report an immobilized enzyme-catalyzed batch and continuous-flow synthesis of optically pure ethyl(R)-pantothenate((R)-PaOEt),the direct precursor of d-pantothenic acid.Firstly,a ketoreductase mutant designated as M2,carrying two-point mutations of F97L and M242F relative to the wild-type SSCR,was constructed by site-directed mutagenesis,exhibited simultaneously improved activity toward ethyl 2′-ketopantothenate(K-PaOEt)and isopropanol,and could effectively catalyze the stereoselective reduction of K-PaOEt to(R)-PaOEt by using isopropanol as the sacrificial co-substrate to regenerate NADPH.After screening six commercially available carriers,an amino resin LXTE-700 was identified as the best solid support for the immobilization of M2 via the glutaraldehyde activation method.Upon optimization of the immobilization process and reaction conditions,the fabricated immobilized enzyme M2@amino resin demonstrated excellent recyclability and reusability,with the complete conversion of K-PaOEt to(R)-PaOEt being still realized after 12 cycles of reuse.Finally,M2@amino resin-catalyzed synthesis of(R)-PaOEt was successfully implemented in continuous-flow,accomplishing a 6.3 times higher space-time yield than that with the batch synthesis(529.2 versus 84 g L^(-1) d^(-1)).Our developed flow biocatalysis system also features an outstanding operational stability,as evidenced by the 100%conversion rate achieved after 15 consecutive days of operation.
基金supported by the National Natural Science Foundation of China(No.52274318).
文摘A full-sectional microstructure characterization method was developed to investigate the formation of coarse slag rims during the continuous casting of hypo-peritectic steel.The cross-sectional microstructural analysis of typical slag rims for two highly crystalline powders revealed that their formation was primarily driven by the solidification of the liquid slag.Distinct differences were observed in the microstructures of slag rims from the two powders.Powder A(characterized by a higher breaking temperature and viscosity)displayed alternating lamellar microstructures of coarse and fine phases,with the coarse phases composed of akermanite-gehlenite transition phases.In contrast,powder B(with a lower breaking temperature and viscosity)predominantly comprised regular akermanite-gehlenite crystals interspersed with a certain amount of glassy phases.Numerical simulations of a three-phase fluid flow coupled with heat transfer indicate that slag rim formation correlates with mold oscillation.Solidification of the liquid slag at the slag rim front predominantly occurs during the negative stroke of the mold oscillation.The average heating rate during the ascending stage of the mold reaches approximately 100 K·s^(−1),whereas the average cooling rate during the descending stage attains 400 K·s^(−1).This temperature variation leads to the formation of lamellar microstructures,whereas the ascending stage promotes the formation of coarse structures and thicker slag rims.Based on the powder properties,two distinct formation pathways exist for highly crystalline mold powders.For the powders with a higher breaking temperature,higher viscosity,and narrower solidification range(powder A),coarse microstructures and thicker slag rims were preferentially formed.For powders with lower breaking temperature and viscosity and wider solidification ranges(powder B),the liquid slag resisted rapid solidification,and the extended mushy zone allowed the partial liquid slag to persist at the slag rim front,promoting the formation of a thin slag rim.This study enhances the understanding of slag rim formation in highly crystalline mold powders and provides critical insights into the control of longitudinal surface cracks in hypo-peritectic steel.
文摘This paper deals with the numerical solutions of two-dimensional(2D)semi-linear reaction-diffusion equations(SLRDEs)with piecewise continuous argument(PCA)in reaction term.A high-order compact difference method called Ⅰ-type basic scheme is developed for solving the equations and it is proved under the suitable conditions that this method has the computational accuracy O(τ^(2)+h_(x)^(4)+h_(y)^(4)),where τ,h_(x )and h_(y) are the calculation stepsizes of the method in t-,x-and y-direction,respectively.With the above method and Newton linearized technique,a Ⅱ-type basic scheme is also suggested.Based on the both basic schemes,the corresponding Ⅰ-and Ⅱ-type alternating direction implicit(ADI)schemes are derived.Finally,with a series of numerical experiments,the computational accuracy and efficiency of the four numerical schemes are further illustrated.
基金supported by the following grants:National Natural Science Foundation of China(grant nos.92354305,32271428,and 32201132)National Key R&D Program of China(grant no.2022YFC3401100)+1 种基金Fund for Knowledge Innovation of Wuhan Science and Technology Bureau(grant no.2022020801010558)Director Fund of WNLO.
文摘The rapid development of super-resolution microscopy has made it possible to observe subcellular structures and dynamic behaviors in living cells with nanoscale spatial resolution, greatly advancing progress in life sciences. As hardware technology continues to evolve, the availability of new fluorescent probes with superior performance is becoming increasingly important. In recent years, fluorescent nanoprobes (FNPs) have emerged as highly promising fluorescent probes for bioimaging due to their high brightness and excellent photostability. This paper focuses on the development and applications of FNPs as probes for live-cell super-resolution imaging. It provides an overview of different super-resolution methods, discusses the performance requirements for FNPs in these methods, and reviews the latest applications of FNPs in the super-resolution imaging of living cells. Finally, it addresses the challenges and future outlook in this field.
基金Supported by Yunnan Province Academician(Expert)Workstation Project,No.202305AF150097the Basic Research Program of Yunnan Province(Kunming Medical University Joint Special Project),No.202101AY070001-276+3 种基金the National Natural Science Foundation of China,No.82160159the Key Project Program of Yunnan Province(Kunming Medical University Joint Special Project),No.202301AY070001-013the Major Science and Technology Project of Yunnan Province,No.202202AA100004the Double First-class University Construction Project of Yunnan University,No.CY22624106.
文摘BACKGROUND Continuous glucose monitoring(CGM)metrics,such as time in range(TIR)and glycemic risk index(GRI),have been linked to various diabetes-related complications,including diabetic foot(DF).AIM To investigate the association between CGM-derived indicators and the risk of DF in individuals with type 2 diabetes mellitus(T2DM).METHODS A total of 591 individuals with T2DM(297 with DF and 294 without DF)were enrolled.Relevant clinical data,complications,comorbidities,hematological parameters,and 72-hour CGM data were collected.Logistic regression analysis was employed to examine the relationship between these measurements and the risk of DF.RESULTS Individuals with DF exhibited higher mean blood glucose(MBG)levels and increased proportions of time above range(TAR),TAR level 1,and TAR level 2,but lower TIR(all P<0.001).Patients with DF had significantly lower rates of achieving target ranges for TIR,TAR,and TAR level 2 than those without DF(all P<0.05).Logistic regression analysis revealed that GRI,MBG,and TAR level 1 were positively associated with DF risk,while TIR was inversely correlated(all P<0.05).Achieving TIR and TAR was inversely correlated with white blood cell count and glycated hemoglobin A1c levels(P<0.05).Additionally,achieving TAR was influenced by fasting plasma glucose,body mass index,diabetes duration,and antidiabetic medication use.CONCLUSION CGM metrics,particularly TIR and GRI,are significantly associated with the risk of DF in T2DM,emphasizing the importance of improved glucose control.
基金supported by the National Natural Science Foundation of China(No.52474355)the Liaoning Province Science and Technology Plan Joint Program(Key Research and Development Program Project),China(Nos.2022JH25/10200003 and 2023JH2/101800058).
文摘The application of liquid core reduction(LCR)technology in thin slab continuous casting can refine the internal microstruc-tures of slabs and improve their production efficiency.To avoid crack risks caused by large deformation during the LCR process and to minimize the thickness of the slab in bending segments,the maximum theoretical reduction amount and the corresponding reduction scheme for the LCR process must be determined.With SPA-H weathering steel as a specific research steel grade,the distributions of tem-perature and deformation fields of a slab with the LCR process were analyzed using a three-dimensional thermal-mechanical finite ele-ment model.High-temperature tensile tests were designed to determine the critical strain of corner crack propagation and intermediate crack initiation with various strain rates and temperatures,and a prediction model of the critical strain for two typical cracks,combining the effects of strain rate and temperature,was proposed by incorporating the Zener-Hollomon parameter.The crack risks with different LCR schemes were calculated using the crack risk prediction model,and the maximum theoretical reduction amount for the SPA-H slab with a transverse section of 145 mm×1600 mm was 41.8 mm,with corresponding reduction amounts for Segment 0 to Segment 4 of 15.8,7.3,6.5,6.4,and 5.8 mm,respectively.
基金supported by the National Key R&D Program of China(Grant No.2023YFC3008404)the National Key Research and Development Program,China(Grant No.2017YFD0800501)the National Natural Science Foundation of China(No.41790443).
文摘During extensive gully land consolidation projects on China's Loess Plateau,many loess-bedrock fill slopes were formed,which frequently experience shallow landslides induced by rainfall.However,studies on loess-bedrock slope failure triggered by continuous heavy rainfall are limited,and the role of the soilerock interface between the original bedrock slope and fill slope in the hydrological and failure process of the slope remains unclear.In this study,we conducted a continuous rainfall model test on a loess-bedrock fill slope.During the test,the responses of volume water content,pore pressure,micro deformation,and movement of the infiltration front were observed.The hydrological process and failure mechanism were then analysed.The findings suggest that the soilerock interface is a predominant infiltration surface within the slope.Rainfall infiltration rates at the interface reach 1.24-2.80 times those of the fill slope,with peak interfacial pore water pressure exceeding that of the loess fill.Furthermore,the infiltration front moves rapidly along the interface toward the bottom of the slope,reducing interfacial cohesion between bedrock and loess.The slope failure modes are summarised into three phases:local failure→flow slide and crack penetration→multistage block retrogressive slides.The cracks generated at the slope surface serve as key determinants of the geometry and scale of shallow landslides.Therefore,we recommend targeted engineering interventions to mitigate the instability and erosion of loessebedrock fill slopes.
基金supported by the National Key Research and Development Program of China (Grant No.2022YFB3706801)the National Natural Science Foundation of China (Grant Nos.U2341253,52371019,U2241232)+2 种基金the Dalian High-level Talents Innovation Support Program (Grant No.2021RD06)the Applied Basic Research Program of Liaoning Province (Grant No.2022JH2/101300003)the Natural Science Foundation of Liaoning Province (Grant Nos.2022-BS-262,JYTMS20230031)。
文摘Based on thermodynamic calculations and continuous rheological extrusion(CRE)technology,Al-Ti-V-B master alloys were designed and prepared.The morphology and the distribution of the refined phases in the master alloys were analyzed by XRD,SEM,and TEM.The effects of master alloy addition and holding time on the microstructure and mechanical properties of A356 alloy were investigated.Under the optimum refiner addition of 0.3wt.%and the holding time of 20 min,the average grain size of the refined A356 alloy is 151.8±9.11μm,89.62%lower than that of original A356 alloy.The tensile strength and elongation of as-cast A356refined alloy are 196.11 MPa and 5.75%,respectively.After T6 treatment,the tensile strength and elongation of A356 refined alloy are 290.1 MPa and 3.09%,respectively.The fracture morphology is characterized by a predominance of along-crystal fracture with a small amount of through-crystal fracture,attributed to the refined grains.Finer grains promote crack path deflection and localized plastic deformation,enhancing energy dissipation and reducing the tendency for brittle fracture.This study provides a novel approach to improving the mechanical properties of A356 alloy through grain refinement using CRE Al-Ti-V-B master alloy.
文摘Image super-resolution reconstruction technology is currently widely used in medical imaging,video surveillance,and industrial quality inspection.It not only enhances image quality but also improves details and visual perception,significantly increasing the utility of low-resolution images.In this study,an improved image superresolution reconstruction model based on Generative Adversarial Networks(SRGAN)was proposed.This model introduced a channel and spatial attention mechanism(CSAB)in the generator,allowing it to effectively leverage the information from the input image to enhance feature representations and capture important details.The discriminator was designed with an improved PatchGAN architecture,which more accurately captured local details and texture information of the image.With these enhanced generator and discriminator architectures and an optimized loss function design,this method demonstrated superior performance in image quality assessment metrics.Experimental results showed that this model outperforms traditional methods,presenting more detailed and realistic image details in the visual effects.
文摘Significant advancements have been achieved in the field of Single Image Super-Resolution(SISR)through the utilization of Convolutional Neural Networks(CNNs)to attain state-of-the-art performance.Recent efforts have explored the incorporation of Transformers to augment network performance in SISR.However,the high computational cost of Transformers makes them less suitable for deployment on lightweight devices.Moreover,the majority of enhancements for CNNs rely predominantly on small spatial convolutions,thereby neglecting the potential advantages of large kernel convolution.In this paper,the authors propose a Multi-Perception Large Kernel convNet(MPLKN)which delves into the exploration of large kernel convolution.Specifically,the authors have architected a Multi-Perception Large Kernel(MPLK)module aimed at extracting multi-scale features and employ a stepwise feature fusion strategy to seamlessly integrate these features.In addition,to enhance the network's capacity for nonlinear spatial information processing,the authors have designed a Spatial-Channel Gated Feed-forward Network(SCGFN)that is capable of adapting to feature interactions across both spatial and channel dimensions.Experimental results demonstrate that MPLKN outperforms other lightweight image super-resolution models while maintaining a minimal number of parameters and FLOPs.
基金supported by National Key Research and Development Program of China(Grant No.2023YFB4604100)National Key Research and Development Program of China(Grant No.2022YFB3806104)+4 种基金Key Research and Development Program in Shaanxi Province(Grant No.2021LLRH-08-17)Young Elite Scientists Sponsorship Program by CAST(No.2023QNRC001)K C Wong Education Foundation of ChinaYouth Innovation Team of Shaanxi Universities of ChinaKey Research and Development Program of Shaanxi Province(Grant 2021LLRH-08-3.1).
文摘Ensuring the consistent mechanical performance of three-dimensional(3D)-printed continuous fiber-reinforced composites is a significant challenge in additive manufacturing.The current reliance on manual monitoring exacerbates this challenge by rendering the process vulnerable to environmental changes and unexpected factors,resulting in defects and inconsistent product quality,particularly in unmanned long-term operations or printing in extreme environments.To address these issues,we developed a process monitoring and closed-loop feedback control strategy for the 3D printing process.Real-time printing image data were captured and analyzed using a well-trained neural network model,and a real-time control module-enabled closed-loop feedback control of the flow rate was developed.The neural network model,which was based on image processing and artificial intelligence,enabled the recognition of flow rate values with an accuracy of 94.70%.The experimental results showed significant improvements in both the surface performance and mechanical properties of printed composites,with three to six times improvement in tensile strength and elastic modulus,demonstrating the effectiveness of the strategy.This study provides a generalized process monitoring and feedback control method for the 3D printing of continuous fiber-reinforced composites,and offers a potential solution for remote online monitoring and closed-loop adjustment in unmanned or extreme space environments.
基金supported by Sichuan Science and Technology Program[2023YFSY0026,2023YFH0004].
文摘Recent Super-Resolution(SR)algorithms often suffer from excessive model complexity,high computational costs,and limited flexibility across varying image scales.To address these challenges,we propose DDNet,a dynamic and lightweight SR framework designed for arbitrary scaling factors.DDNet integrates a residual learning structure with an Adaptively fusion Feature Block(AFB)and a scale-aware upsampling module,effectively reducing parameter overhead while preserving reconstruction quality.Additionally,we introduce DDNetGAN,an enhanced variant that leverages a relativistic Generative Adversarial Network(GAN)to further improve texture realism.To validate the proposed models,we conduct extensive training using the DIV2K and Flickr2K datasets and evaluate performance across standard benchmarks including Set5,Set14,Urban100,Manga109,and BSD100.Our experiments cover both symmetric and asymmetric upscaling factors and incorporate ablation studies to assess key components.Results show that DDNet and DDNetGAN achieve competitive performance compared with mainstream SR algorithms,demonstrating a strong balance between accuracy,efficiency,and flexibility.These findings highlight the potential of our approach for practical real-world super-resolution applications.
基金supported by the following grants:National Key R&D Program of China(Grant no.2022YFC3401100)National Natural Science Foundation of China(Grant nos.32271428,92054110,32201132 and 31600692).
文摘Blood cells are the most integral part of the body,which are made up of erythrocytes,platelets and white blood cells.The examination of subcellular structures and proteins within blood cells at the nanoscale can provide valuable insights into the health status of an individual,accurate diagnosis,and efficient treatment strategies for diseases.Super-resolution microscopy(SRM)has recently emerged as a cutting-edge tool for the study of blood cells,providing numerous advantages over traditional methods for examining subcellular structures and proteins.In this paper,we focus on outlining the fundamental principles of various SRM techniques and their applications in both normal and diseased states of blood cells.Furthermore,future prospects of SRM techniques in the analysis of blood cells are also discussed.
基金supported by the National Natural Science Foundation of China(62175034,62175036,32271510)the National Key R&D Program of China(2021YFF0502900)+2 种基金the Science and Technology Research Program of Shanghai(Grant No.19DZ2282100)the Shanghai Key Laboratory of Metasurfaces for Light Manipulation(23dz2260100)the Shanghai Engineering Technology Research Center of Hair Medicine(19DZ2250500).
文摘A new scheme of super-resolution optical fluctuation imaging(SOFI)is proposed to broaden its application in the high-order cumulant reconstruction by optimizing blinking characteristics,eliminating noise in raw data and applying multi-resolution analysis in cumulant reconstruction.A motor-driven rotating mask optical modulation system is designed to adjust the excitation lightfield and allows for fast deployment.Active-modulated fluorescence fluctuation superresolution microscopy with multi-resolution analysis(AMF-MRA-SOFI)demonstrates enhanced resolution ability and reconstruction quality in experiments performed on sample of conventional dyes,achieving a resolution of 100 nm in the fourth order compared to conventional SOFI reconstruction.Furthermore,our approach combining expansion super-resolution achieved a resolution at-57 nm.
基金the National Natural Science Foundation(NNSF)of China under Grant 41927801.
文摘The evaluation of adsorption states and shale gas content in shale fractures and pores relies on the analysis of these fractures and pores.Scanning electron microscopy images are commonly used for shale analysis;however,their low resolution,particularly the loss of high-frequency information at pore edges,presents challenges in analyzing fractures and pores in shale gas reservoirs.This study introduced a novel neural network called the spatial-spectral domain attention network(SSDAN),which employed spatial and spectral domain attention mechanisms to extract features and restore information in parallel.The network generated super-resolution images through a fusion module that included CNN-based spatial blocks for pixel-level image information recovery,spectral blocks to process Fourier transform information of images and enhance high-frequency recovery,and an adaptive vision transformer to process Fourier transform block information,eliminating the need for a preset image size.The SSDAN model demonstrated exceptional performance in comparative experiments on marine shale and marine continental shale datasets,achieving optimal performance on key indicators such as peak signal-to-noise ratio,structural similarity,learned perceptual image patch similarity,and Frechet inception distance while also exhibiting superior visual performance in pore recovery.Ablation experiments further confirmed the effectiveness of the spatial blocks,channel attention,spectral blocks,and frequency loss function in the model.The SSDAN model showed remarkable capability in enhancing the resolution of shale gas reservoir images and restoring high-frequency information at pore edges,thereby validating its effectiveness in unconventional natural gas reservoir analyses.
基金supported by the‘Pioneer’and‘Leading Goose’R&D Program of Zhejiang(Grant No.2023C02018)Zhejiang Provincial Natural Science Foundation of China(Grant No.LTGN23D010002)+2 种基金National Natural Science Foundation of China(Grant No.42371385)Funds of the Natural Science Foundation of Hangzhou(Grant No.2024SZRYBD010001)Nanxun Scholars Program of ZJWEU(Grant No.RC2022010755).
文摘Plant diseases are a major threat that can severely impact the production of agriculture and forestry.This can lead to the disruption of ecosystem functions and health.With its ability to capture continuous narrow-band spectra,hyperspectral technology has become a crucial tool to monitor crop diseases using remote sensing.However,existing continuous wavelet analysis(CWA)methods suffer from feature redundancy issues,while the continuous wavelet projection algorithm(CWPA),an optimization approach for feature selection,has not been fully validated to monitor plant diseases.This study utilized rice bacterial leaf blight(BLB)as an example by evaluating the performance of four wavelet basis functions-Gaussian2,Mexican hat,Meyer,andMorlet-within theCWAandCWPAframeworks.Additionally,the classification models were constructed using the k-nearest neighbors(KNN),randomforest(RF),and Naïve Bayes(NB)algorithms.The results showed the following:(1)Compared to traditional CWA,CWPA significantly reduced the number of required features.Under the CWPA framework,almost all the model combinations achieved maximum classification accuracy with only one feature.In contrast,the CWA framework required three to seven features.(2)Thechoice of wavelet basis functions markedly affected the performance of themodel.Of the four functions tested,the Meyer wavelet demonstrated the best overall performance in both the CWPA and CWA frameworks.(3)Under theCWPAframework,theMeyer-KNNandMeyer-NBcombinations achieved the highest overall accuracy of 93.75%using just one feature.In contrast,under the CWA framework,the CWA-RF combination achieved comparable accuracy(93.75%)but required six features.This study verified the technical advantages of CWPA for monitoring crop diseases,identified an optimal wavelet basis function selection scheme,and provided reliable technical support to precisely monitor BLB in rice(Oryza sativa).Moreover,the proposed methodological framework offers a scalable approach for the early diagnosis and assessment of plant stress,which can contribute to improved accuracy and timeliness when plant stress is monitored.
基金funded in part by theHenan ProvinceKeyR&DProgramProject,“Research and Application Demonstration of Class Ⅱ Superlattice Medium Wave High Temperature Infrared Detector Technology”under Grant No.231111210400.
文摘Infrared imaging technology has been widely adopted in various fields,such as military reconnaissance,medical diagnosis,and security monitoring,due to its excellent ability to penetrate smoke and fog.However,the prevalent low resolution of infrared images severely limits the accurate interpretation of their contents.In addition,deploying super-resolution models on resource-constrained devices faces significant challenges.To address these issues,this study proposes a lightweight super-resolution network for infrared images based on an adaptive attention mechanism.The network’s dynamic weighting module automatically adjusts the weights of the attention and nonattention branch outputs based on the network’s characteristics at different levels.Among them,the attention branch is further subdivided into pixel attention and brightness-texture attention,which are specialized for extracting the most informative features in infrared images.Meanwhile,the non-attention branch supplements the extraction of those neglected features to enhance the comprehensiveness of the features.Through ablation experiments,we verify the effectiveness of the proposed module.Finally,through experiments on two datasets,FLIR and Thermal101,qualitative and quantitative results demonstrate that the model can effectively recover high-frequency details of infrared images and significantly improve image resolution.In detail,compared with the suboptimal method,we have reduced the number of parameters by 30%and improved the model performance.When the scale factor is 2,the peak signal-tonoise ratio of the test datasets FLIR and Thermal101 is improved by 0.09 and 0.15 dB,respectively.When the scale factor is 4,it is improved by 0.05 and 0.09 dB,respectively.In addition,due to the lightweight design of the network structure,it has a low computational cost.It is suitable for deployment on edge devices,thus effectively enhancing the sensing performance of infrared imaging devices.
