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
<div style="text-align:justify;"> Due to the wave characteristics of light, diffraction occurs when the light passes through the optical system, so that the resolution of the ordinary far-field optical...<div style="text-align:justify;"> Due to the wave characteristics of light, diffraction occurs when the light passes through the optical system, so that the resolution of the ordinary far-field optical system is limited by the size of the Airy disk diameter. There are various factors that cause image quality degradation during system detection and imaging, such as optical system aberrations, atmospheric inter-ference, defocusing, system noise and so on. Super-resolution optical imaging technology is the most innovative breakthrough in the optical imaging and detection field in this century. It goes beyond the resolution limit of ordinary optical systems or detectors, and can get more details and information of the structure, providing unprecedented tools for various fields. Compared with ordinary optical systems, super-resolution systems have very high requirements on the signals to be detected, which cannot be met by ordinary detection techniques. Vacuum photoelectric detection and imaging technology is equipped with the characteristics of high sensitivity and fast response. It is widely used in super-resolution systems and has played a great role in super-resolution systems. In this paper, the principles and structure of the image-converter streak camera super-resolution system, scanning electron microscopy super-resolution system and laser scanning confocal super-resolution system will be sorted out separately, and the essential role of the vacuum photoelectric detection technology in the ultra-microscopic sys-tem will be analyzed. </div>展开更多
Terahertz biotechnology has been increasingly applied in various biomedical fields and has especially shown great potential for application in brain sciences.In this article,we review the development of terahertz biot...Terahertz biotechnology has been increasingly applied in various biomedical fields and has especially shown great potential for application in brain sciences.In this article,we review the development of terahertz biotechnology and its applications in the field of neuropsychiatry.Available evidence indicates promising prospects for the use of terahertz spectroscopy and terahertz imaging techniques in the diagnosis of amyloid disease,cerebrovascular disease,glioma,psychiatric disease,traumatic brain injury,and myelin deficit.In vitro and animal experiments have also demonstrated the potential therapeutic value of terahertz technology in some neuropsychiatric diseases.Although the precise underlying mechanism of the interactions between terahertz electromagnetic waves and the biosystem is not yet fully understood,the research progress in this field shows great potential for biomedical noninvasive diagnostic and therapeutic applications.However,the biosafety of terahertz radiation requires further exploration regarding its two-sided efficacy in practical applications.This review demonstrates that terahertz biotechnology has the potential to be a promising method in the field of neuropsychiatry based on its unique advantages.展开更多
Subgrade engineering is a fundamental aspect of infrastructure construction in China.As the primary structural element responsible for bearing and distributing traffic loads,the subgrade must not only withstand the su...Subgrade engineering is a fundamental aspect of infrastructure construction in China.As the primary structural element responsible for bearing and distributing traffic loads,the subgrade must not only withstand the substantial pressures exerted by vehicles,trains,and other forms of transportation,but also efficiently transfer these loads to the underlying foundation,ensuring the stability and longevity of the roadway.In recent years,advancements in subgrade engineering technology have propelled the industry towards smarter,greener,and more sustainable practices,particularly in the areas of intelligent monitoring,disaster management,and innovative construction methods.This paper reviews the application and methodologies of intelligent testing equipment,including cone penetration testing(CPT)devices,soil resistivity testers,and intelligent rebound testers,in subgrade engineering.It examines the operating principles,advantages,limitations,and application ranges of these tools in subgrade testing.Additionally,the paper evaluates the practical use of advanced equipment from both domestic and international perspectives,addressing the challenges encountered by various instruments in realworld applications.These devices enable precise,comprehensive testing and evaluation of subgrade conditions at different stages,providing real-time data analysis and intelligent early warnings.This supports effective subgrade health management and maintenance.As intelligent technologies continue to evolve and integrate,these tools will increasingly enhance the accuracy,efficiency,and sustainability of subgrade monitoring.展开更多
As artificial intelligence(AI)technology has continued to develop,its efficient data processing and pattern recognition capabilities have significantly improved the precision and speed of decision-making processes,and...As artificial intelligence(AI)technology has continued to develop,its efficient data processing and pattern recognition capabilities have significantly improved the precision and speed of decision-making processes,and it has been widely applied across various fields.In the field of astronomy,AI techniques have demonstrated unique advantages,particularly in the identification of pulsars and their candidates.AI is able to address the challenges of pulsar celestial body identification and classification because of its accuracy and efficiency.This paper systematically surveys commonly used AI models for pulsar candidate identification,analyzing and discussing the typical applications of machine learning,artificial neural networks,convolutional neural networks,and generative adversarial networks in candidate identification.Furthermore,it explores how th.e introduction of AI techniques not only enhances the efficiency and accuracy of pulsar identification but also provides new perspectives and tools for pulsar survey data processing,thus playing a significant role in advancing pulsar research and the field of astronomy.展开更多
This study investigated the application and the application value of intelligent emergency in emergency management in the big data environment.It addresses the neglect of the application value(performance)measurement ...This study investigated the application and the application value of intelligent emergency in emergency management in the big data environment.It addresses the neglect of the application value(performance)measurement of intelligent emergency,further improving the effectiveness of intelligent emergency management.First,approximately 3,900 documents from the intelligent emergency field are analyzed to determine the future research trend in intelligent emergency management.The socio-technical theory concerning technical and social systems is introduced.The emergency management system concepts of“technology enabling”and“enabling value creation”are defined according to bibliometric analysis and socio-technical theory.Second,a research framework that includes technology enabling and enabling value creation for the decision-making paradigm in emergency management according to the big data environment is constructed.A detailed analysis approach from intelligent emergency technology enabling to enabling value creation in emergency management is proposed.Finally,earthquake disasters are taken as examples,and specific analyses of the intelligent emergency enabling and enabling value creation are explored;enabling value creation is discussed based on measurable indicators.The clear concept of emergency management system technology enabling and enabling value creation,as well as the detailed analysis approach from intelligent emergency technology enabling to enabling value creation,provide a theoretical bases for scholars and practitioners to evaluate the value(performance)of intelligent emergency for the first time.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
Surface engineering plays a crucial role in improving the performance of high energy materials,and polydopamine(PDA)is widely used in the field of energetic materials for surface modification and functionalization.In ...Surface engineering plays a crucial role in improving the performance of high energy materials,and polydopamine(PDA)is widely used in the field of energetic materials for surface modification and functionalization.In order to obtain high-quality HMX@PDA-based PBX explosives with high sphericity and a narrow particle size distribution,composite microspheres were prepared using co-axial droplet microfluidic technology.The formation mechanism,thermal behavior,mechanical sensitivity,electrostatic spark sensitivity,compressive strength,and combustion performance of the microspheres were investigated.The results show that PDA can effectively enhance the interfacial interaction between the explosive particles and the binder under the synergistic effect of chemical bonds and the physical"mechanical interlocking"structure.Interface reinforcement causes the thermal decomposition temperature of the sample microspheres to move to a higher temperature,with the sensitivity to impact,friction,and electrostatic sparks(for S-1)increasing by 12.5%,31.3%,and 81.5%respectively,and the compressive strength also increased by 30.7%,effectively enhancing the safety performance of the microspheres.Therefore,this study provides an effective and universal strategy for preparing high-quality functional explosives,and also provides some reference for the safe use of energetic materials in practical applications.展开更多
In recent years,perovskite solar cells(PSCs)have garnered significant attention as a potential mainstream technology in the future photovol-taic(PV)market.This is primarily attributed to their salient advantages inclu...In recent years,perovskite solar cells(PSCs)have garnered significant attention as a potential mainstream technology in the future photovol-taic(PV)market.This is primarily attributed to their salient advantages including high efficiency,low cost,and ease of preparation.Nota-bly,the power conversion efficiency(PCE)of PSCs has experienced a remarkable increase from 3.8%in 2009 to over 26%at present.Conse-quently,the adoption of roll-to-roll(R2R)technology for PSCs is considered a crucial step towards their successful commercialization.This arti-de reviews the diverse substrates,scalable deposition techniques(such as solution-based knife-coating and spraying technology),and optimiza.tion procedures employed in recent years to enhance device performance within the R2R process.Additionally,novel perspectives are presented to enrich the existing knowledge in this field.展开更多
This article explores the design of a wireless fire alarm system supported by advanced data fusion technology.It includes discussions on the basic design ideas of the wireless fire alarm system,hardware design analysi...This article explores the design of a wireless fire alarm system supported by advanced data fusion technology.It includes discussions on the basic design ideas of the wireless fire alarm system,hardware design analysis,software design analysis,and simulation analysis,all supported by data fusion technology.Hopefully,this analysis can provide some reference for the rational application of data fusion technology to meet the actual design and application requirements of the system.展开更多
Purpose–This study summarizes the overall situation of the resources of the national science and technology innovation platform in the railway industry,including the distribution of platform types,supporting institut...Purpose–This study summarizes the overall situation of the resources of the national science and technology innovation platform in the railway industry,including the distribution of platform types,supporting institutions,construction sites,professional fields,etc.,to provide a reference for the further improvement and optimization of the national science and technology innovation platform system in the railway industry.Design/methodology/approach–Through literature review,field investigation,expert consultation and other methods,this paper systematically investigates and analyzes the development status of the national science and technology innovation platform in the railway industry.Findings–Taking the national science and technology innovation platform of the railway industry as the research object,this paper investigates and analyzes the construction,development and distribution of the national science and technology innovation platform of railway industry over the years.And the National Engineering Research Center of High-speed Railway and Urban Rail Transit System Technology was taken as an example to introduce its operation effect.Originality/value–China Railway has made great development achievements,with the construction and development of national science and technology innovation platform in the railway industry.In recent years,a large number of national science and technology innovation platforms have been built in the railway industry,which play an important role in railway technological innovation,standard setting and commodification,and Railway Sciences provide strong support for railway technology development.展开更多
Tungsten/molybdenum alloys are widely utilized in the nuclear industry,aerospace and various other fields due to their high melting points and strength characteristics.However,poor sinterability and processability mak...Tungsten/molybdenum alloys are widely utilized in the nuclear industry,aerospace and various other fields due to their high melting points and strength characteristics.However,poor sinterability and processability make it difficult to manufacture largesize or complex-shaped parts.Hence,an in-depth study on the welding technology of tungsten/molybdenum alloys is urgent.An introduction of tungsten/molybdenum alloy welding defects and joining process was provided,along with recent advancements in brazing,spark plasma sintering diffusion bonding,electron beam welding and laser beam welding.The latest progress in alloy doping treatment applied to tungsten/molybdenum alloy dissimilar welding was also discussed,and existing welding problems were pointed out.The development prospects of weldability of tungsten/molybdenum alloy by various joining technologies were forecasted,thereby furnishing a theoretical and practical found.展开更多
In this work,the generation of high signal-to-noise ratio(SNR)single-frequency microwave signal without noise sidebands is demonstrated based on the interaction of integrated all-fiber lasers.The microwave signals are...In this work,the generation of high signal-to-noise ratio(SNR)single-frequency microwave signal without noise sidebands is demonstrated based on the interaction of integrated all-fiber lasers.The microwave signals are generated by the interference between a narrow linewidth Brillouin pump light from a single-frequency laser and the Stokes light generated by it.Firstly,the linewidths of the Stokes lights are compressed to~43 Hz based on the stimulated Brillouin scattering(SBS)effect,which ensures that the frequency noise is as low as possible.And then,the relative intensity noise(RIN)of the first order Stokes light is reduced by 21 dB/Hz based on the noise dynamics principle in cascaded SBS effect.By simultaneously reducing the frequency noise and the intensity noise of the coherent signals,the noise sidebands of microwave signals are completely suppressed.As result,the SNR of the microwave signal is improved from 48 dB to 84 dB at the first-order Brillouin frequency shift of 9.415 GHz.Meanwhile,a microwave signal with a SNR of 70 dB is generated at the second-order Brillouin frequency shift of 18.827 GHz.This kind of microwave signals with narrow linewidth and high SNR can provide higher detection resolution and higher transmission efficiency for applications on radar,satellite communication and so on.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
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
This study investigates the inundation depths of urban floods induced by real storm events,focusing on the development and assessment of super-resolution model based on ensemble learning methods.Unlike traditional dee...This study investigates the inundation depths of urban floods induced by real storm events,focusing on the development and assessment of super-resolution model based on ensemble learning methods.Unlike traditional deep neural networks which require extensive training and high parameterization,this study utilizes ensemble learning model to reconstruct high-resolution flood predictions from low-resolution hydrodynamic simulations.Hydrodynamic modeling results of real pluvial flood event at various spatial resolution are used for constructing datasets and for training and testing the point-based super-resolution model.Influencing factors related to urban terrain,subsurface,rainfall inputs and the hydrodynamic modeling results at coarser resolutions are used as features in the super-resolution model on basis of Random Forest,in which hyperparameters are tuned with Bayesian optimization method.The trained super-resolution models effectively reconstruct high-resolution inundation conditions from 30 m to 5 m coarse resolution inputs,highlighting an increase in correlation coefficients and a decrease in root mean squared error(RMSE)as resolution improves.Dominant influencing factors in the super-resolution models are identified together with variances in their contributions to the model performance.Two optimization approaches are applied to enhance accuracy and mitigate overestimation at coarse resolutions for the super-resolution models.The first integrates outputs from various coarse resolution models as features,notably reducing overestimation,especially with finer 5 m resolutions.The second employs ensemble modeling with super-resolution models from different datasets,which improves the performance across all tested resolutions,demonstrating the robustness of combining multiple predictive models for better flood forecasting in urban environments.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
“Wow,this robot is so cool!”In the Hangzhou Shenhao Technology Co.,Ltd.showroom,a humanoid robot gracefully performed Tai Chi,grabbing the attention of a visiting delegation from ASEAN.In September,the group of scho...“Wow,this robot is so cool!”In the Hangzhou Shenhao Technology Co.,Ltd.showroom,a humanoid robot gracefully performed Tai Chi,grabbing the attention of a visiting delegation from ASEAN.In September,the group of scholars from regional think tanks and journalists toured Hangzhou,Jinhua,and Huzhou in east China’s Zhejiang Province.Along the way,they enjoyed an up-close look at how digital and intelligent technologies are subtly changing everyday life.展开更多
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<div style="text-align:justify;"> Due to the wave characteristics of light, diffraction occurs when the light passes through the optical system, so that the resolution of the ordinary far-field optical system is limited by the size of the Airy disk diameter. There are various factors that cause image quality degradation during system detection and imaging, such as optical system aberrations, atmospheric inter-ference, defocusing, system noise and so on. Super-resolution optical imaging technology is the most innovative breakthrough in the optical imaging and detection field in this century. It goes beyond the resolution limit of ordinary optical systems or detectors, and can get more details and information of the structure, providing unprecedented tools for various fields. Compared with ordinary optical systems, super-resolution systems have very high requirements on the signals to be detected, which cannot be met by ordinary detection techniques. Vacuum photoelectric detection and imaging technology is equipped with the characteristics of high sensitivity and fast response. It is widely used in super-resolution systems and has played a great role in super-resolution systems. In this paper, the principles and structure of the image-converter streak camera super-resolution system, scanning electron microscopy super-resolution system and laser scanning confocal super-resolution system will be sorted out separately, and the essential role of the vacuum photoelectric detection technology in the ultra-microscopic sys-tem will be analyzed. </div>
基金supported by grants from the National Key R&D Program of China,No.2017YFC0909200(to DC)the National Natural Science Foundation of China,No.62075225(to HZ)+1 种基金Zhejiang Provincial Medical Health Science and Technology Project,No.2023XY053(to ZP)Zhejiang Provincial Traditional Chinese Medical Science and Technology Project,No.2023ZL703(to ZP).
文摘Terahertz biotechnology has been increasingly applied in various biomedical fields and has especially shown great potential for application in brain sciences.In this article,we review the development of terahertz biotechnology and its applications in the field of neuropsychiatry.Available evidence indicates promising prospects for the use of terahertz spectroscopy and terahertz imaging techniques in the diagnosis of amyloid disease,cerebrovascular disease,glioma,psychiatric disease,traumatic brain injury,and myelin deficit.In vitro and animal experiments have also demonstrated the potential therapeutic value of terahertz technology in some neuropsychiatric diseases.Although the precise underlying mechanism of the interactions between terahertz electromagnetic waves and the biosystem is not yet fully understood,the research progress in this field shows great potential for biomedical noninvasive diagnostic and therapeutic applications.However,the biosafety of terahertz radiation requires further exploration regarding its two-sided efficacy in practical applications.This review demonstrates that terahertz biotechnology has the potential to be a promising method in the field of neuropsychiatry based on its unique advantages.
基金supported by the National Natural Science Foundation of China for Distinguished Young Scholars(Grant No.42225206)National Natural Science Foundation of China(42207180,42477209,42302320).
文摘Subgrade engineering is a fundamental aspect of infrastructure construction in China.As the primary structural element responsible for bearing and distributing traffic loads,the subgrade must not only withstand the substantial pressures exerted by vehicles,trains,and other forms of transportation,but also efficiently transfer these loads to the underlying foundation,ensuring the stability and longevity of the roadway.In recent years,advancements in subgrade engineering technology have propelled the industry towards smarter,greener,and more sustainable practices,particularly in the areas of intelligent monitoring,disaster management,and innovative construction methods.This paper reviews the application and methodologies of intelligent testing equipment,including cone penetration testing(CPT)devices,soil resistivity testers,and intelligent rebound testers,in subgrade engineering.It examines the operating principles,advantages,limitations,and application ranges of these tools in subgrade testing.Additionally,the paper evaluates the practical use of advanced equipment from both domestic and international perspectives,addressing the challenges encountered by various instruments in realworld applications.These devices enable precise,comprehensive testing and evaluation of subgrade conditions at different stages,providing real-time data analysis and intelligent early warnings.This supports effective subgrade health management and maintenance.As intelligent technologies continue to evolve and integrate,these tools will increasingly enhance the accuracy,efficiency,and sustainability of subgrade monitoring.
基金supported by the National Key R&D Program of China(2021YFC2203502 and 2022YFF0711502)the National Natural Science Foundation of China(NSFC)(12173077)+4 种基金the Tianshan Talent Project of Xinjiang Uygur Autonomous Region(2022TSYCCX0095 and 2023TSYCCX0112)the Scientific Instrument Developing Project of the Chinese Academy of Sciences(PTYQ2022YZZD01)China National Astronomical Data Center(NADC)the Operation,Maintenance and Upgrading Fund for Astronomical Telescopes and Facility Instruments,budgeted from the Ministry of Finance of China(MOF)and administrated by the Chinese Academy of Sciences(CAS)Natural Science Foundation of Xinjiang Uygur Autonomous Region(2022D01A360)。
文摘As artificial intelligence(AI)technology has continued to develop,its efficient data processing and pattern recognition capabilities have significantly improved the precision and speed of decision-making processes,and it has been widely applied across various fields.In the field of astronomy,AI techniques have demonstrated unique advantages,particularly in the identification of pulsars and their candidates.AI is able to address the challenges of pulsar celestial body identification and classification because of its accuracy and efficiency.This paper systematically surveys commonly used AI models for pulsar candidate identification,analyzing and discussing the typical applications of machine learning,artificial neural networks,convolutional neural networks,and generative adversarial networks in candidate identification.Furthermore,it explores how th.e introduction of AI techniques not only enhances the efficiency and accuracy of pulsar identification but also provides new perspectives and tools for pulsar survey data processing,thus playing a significant role in advancing pulsar research and the field of astronomy.
基金the National Natural Science Foundation of China(Grant No.:71771061).
文摘This study investigated the application and the application value of intelligent emergency in emergency management in the big data environment.It addresses the neglect of the application value(performance)measurement of intelligent emergency,further improving the effectiveness of intelligent emergency management.First,approximately 3,900 documents from the intelligent emergency field are analyzed to determine the future research trend in intelligent emergency management.The socio-technical theory concerning technical and social systems is introduced.The emergency management system concepts of“technology enabling”and“enabling value creation”are defined according to bibliometric analysis and socio-technical theory.Second,a research framework that includes technology enabling and enabling value creation for the decision-making paradigm in emergency management according to the big data environment is constructed.A detailed analysis approach from intelligent emergency technology enabling to enabling value creation in emergency management is proposed.Finally,earthquake disasters are taken as examples,and specific analyses of the intelligent emergency enabling and enabling value creation are explored;enabling value creation is discussed based on measurable indicators.The clear concept of emergency management system technology enabling and enabling value creation,as well as the detailed analysis approach from intelligent emergency technology enabling to enabling value creation,provide a theoretical bases for scholars and practitioners to evaluate the value(performance)of intelligent emergency for the first time.
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 the National Natural Science Foundation of China(Grant No.22005275).
文摘Surface engineering plays a crucial role in improving the performance of high energy materials,and polydopamine(PDA)is widely used in the field of energetic materials for surface modification and functionalization.In order to obtain high-quality HMX@PDA-based PBX explosives with high sphericity and a narrow particle size distribution,composite microspheres were prepared using co-axial droplet microfluidic technology.The formation mechanism,thermal behavior,mechanical sensitivity,electrostatic spark sensitivity,compressive strength,and combustion performance of the microspheres were investigated.The results show that PDA can effectively enhance the interfacial interaction between the explosive particles and the binder under the synergistic effect of chemical bonds and the physical"mechanical interlocking"structure.Interface reinforcement causes the thermal decomposition temperature of the sample microspheres to move to a higher temperature,with the sensitivity to impact,friction,and electrostatic sparks(for S-1)increasing by 12.5%,31.3%,and 81.5%respectively,and the compressive strength also increased by 30.7%,effectively enhancing the safety performance of the microspheres.Therefore,this study provides an effective and universal strategy for preparing high-quality functional explosives,and also provides some reference for the safe use of energetic materials in practical applications.
文摘In recent years,perovskite solar cells(PSCs)have garnered significant attention as a potential mainstream technology in the future photovol-taic(PV)market.This is primarily attributed to their salient advantages including high efficiency,low cost,and ease of preparation.Nota-bly,the power conversion efficiency(PCE)of PSCs has experienced a remarkable increase from 3.8%in 2009 to over 26%at present.Conse-quently,the adoption of roll-to-roll(R2R)technology for PSCs is considered a crucial step towards their successful commercialization.This arti-de reviews the diverse substrates,scalable deposition techniques(such as solution-based knife-coating and spraying technology),and optimiza.tion procedures employed in recent years to enhance device performance within the R2R process.Additionally,novel perspectives are presented to enrich the existing knowledge in this field.
基金Chongqing Engineering University Undergraduate Innovation and Entrepreneurship Training Program Project:Wireless Fire Automatic Alarm System(Project No.:CXCY2024017)Chongqing Municipal Education Commission Science and Technology Research Project:Development and Research of Chongqing Wireless Fire Automatic Alarm System(Project No.:KJQN202401906)。
文摘This article explores the design of a wireless fire alarm system supported by advanced data fusion technology.It includes discussions on the basic design ideas of the wireless fire alarm system,hardware design analysis,software design analysis,and simulation analysis,all supported by data fusion technology.Hopefully,this analysis can provide some reference for the rational application of data fusion technology to meet the actual design and application requirements of the system.
文摘Purpose–This study summarizes the overall situation of the resources of the national science and technology innovation platform in the railway industry,including the distribution of platform types,supporting institutions,construction sites,professional fields,etc.,to provide a reference for the further improvement and optimization of the national science and technology innovation platform system in the railway industry.Design/methodology/approach–Through literature review,field investigation,expert consultation and other methods,this paper systematically investigates and analyzes the development status of the national science and technology innovation platform in the railway industry.Findings–Taking the national science and technology innovation platform of the railway industry as the research object,this paper investigates and analyzes the construction,development and distribution of the national science and technology innovation platform of railway industry over the years.And the National Engineering Research Center of High-speed Railway and Urban Rail Transit System Technology was taken as an example to introduce its operation effect.Originality/value–China Railway has made great development achievements,with the construction and development of national science and technology innovation platform in the railway industry.In recent years,a large number of national science and technology innovation platforms have been built in the railway industry,which play an important role in railway technological innovation,standard setting and commodification,and Railway Sciences provide strong support for railway technology development.
基金National Natural Science Foundation of China(52071165,52475347)National Program of Foreign Experts of China(G2023026003L)+4 种基金China Postdoctoral Fund(2023M740475)Program for Science&Technology Innovation Talents in Universities of Henan Province,China(22HASTIT026)Program for the Top Young Talents of Henan Province,China,Frontier Exploration Projects of Longmen Laboratory,China(LMQYTSKT016)Key Scientific Research Projects of Colleges and Universities in Henan Province,China(24A460008)Key Science and Technology Project of Henan Province,China(242102220064,222102230111)。
文摘Tungsten/molybdenum alloys are widely utilized in the nuclear industry,aerospace and various other fields due to their high melting points and strength characteristics.However,poor sinterability and processability make it difficult to manufacture largesize or complex-shaped parts.Hence,an in-depth study on the welding technology of tungsten/molybdenum alloys is urgent.An introduction of tungsten/molybdenum alloy welding defects and joining process was provided,along with recent advancements in brazing,spark plasma sintering diffusion bonding,electron beam welding and laser beam welding.The latest progress in alloy doping treatment applied to tungsten/molybdenum alloy dissimilar welding was also discussed,and existing welding problems were pointed out.The development prospects of weldability of tungsten/molybdenum alloy by various joining technologies were forecasted,thereby furnishing a theoretical and practical found.
文摘In this work,the generation of high signal-to-noise ratio(SNR)single-frequency microwave signal without noise sidebands is demonstrated based on the interaction of integrated all-fiber lasers.The microwave signals are generated by the interference between a narrow linewidth Brillouin pump light from a single-frequency laser and the Stokes light generated by it.Firstly,the linewidths of the Stokes lights are compressed to~43 Hz based on the stimulated Brillouin scattering(SBS)effect,which ensures that the frequency noise is as low as possible.And then,the relative intensity noise(RIN)of the first order Stokes light is reduced by 21 dB/Hz based on the noise dynamics principle in cascaded SBS effect.By simultaneously reducing the frequency noise and the intensity noise of the coherent signals,the noise sidebands of microwave signals are completely suppressed.As result,the SNR of the microwave signal is improved from 48 dB to 84 dB at the first-order Brillouin frequency shift of 9.415 GHz.Meanwhile,a microwave signal with a SNR of 70 dB is generated at the second-order Brillouin frequency shift of 18.827 GHz.This kind of microwave signals with narrow linewidth and high SNR can provide higher detection resolution and higher transmission efficiency for applications on radar,satellite communication and so on.
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 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 the National Natural Science Foundation of China(Grant Nos.42201026,52201325 and 42407619)the Startup Foundation for Introducing Talent of NUIST(Grant No.2023r009).
文摘This study investigates the inundation depths of urban floods induced by real storm events,focusing on the development and assessment of super-resolution model based on ensemble learning methods.Unlike traditional deep neural networks which require extensive training and high parameterization,this study utilizes ensemble learning model to reconstruct high-resolution flood predictions from low-resolution hydrodynamic simulations.Hydrodynamic modeling results of real pluvial flood event at various spatial resolution are used for constructing datasets and for training and testing the point-based super-resolution model.Influencing factors related to urban terrain,subsurface,rainfall inputs and the hydrodynamic modeling results at coarser resolutions are used as features in the super-resolution model on basis of Random Forest,in which hyperparameters are tuned with Bayesian optimization method.The trained super-resolution models effectively reconstruct high-resolution inundation conditions from 30 m to 5 m coarse resolution inputs,highlighting an increase in correlation coefficients and a decrease in root mean squared error(RMSE)as resolution improves.Dominant influencing factors in the super-resolution models are identified together with variances in their contributions to the model performance.Two optimization approaches are applied to enhance accuracy and mitigate overestimation at coarse resolutions for the super-resolution models.The first integrates outputs from various coarse resolution models as features,notably reducing overestimation,especially with finer 5 m resolutions.The second employs ensemble modeling with super-resolution models from different datasets,which improves the performance across all tested resolutions,demonstrating the robustness of combining multiple predictive models for better flood forecasting in urban environments.
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.
文摘“Wow,this robot is so cool!”In the Hangzhou Shenhao Technology Co.,Ltd.showroom,a humanoid robot gracefully performed Tai Chi,grabbing the attention of a visiting delegation from ASEAN.In September,the group of scholars from regional think tanks and journalists toured Hangzhou,Jinhua,and Huzhou in east China’s Zhejiang Province.Along the way,they enjoyed an up-close look at how digital and intelligent technologies are subtly changing everyday life.
