Although Named Entity Recognition(NER)in cybersecurity has historically concentrated on threat intelligence,vital security data can be found in a variety of sources,such as open-source intelligence and unprocessed too...Although Named Entity Recognition(NER)in cybersecurity has historically concentrated on threat intelligence,vital security data can be found in a variety of sources,such as open-source intelligence and unprocessed tool outputs.When dealing with technical language,the coexistence of structured and unstructured data poses serious issues for traditional BERT-based techniques.We introduce a three-phase approach for improved NER inmulti-source cybersecurity data that makes use of large language models(LLMs).To ensure thorough entity coverage,our method starts with an identification module that uses dynamic prompting techniques.To lessen hallucinations,the extraction module uses confidence-based self-assessment and cross-checking using regex validation.The tagging module links to knowledge bases for contextual validation and uses SecureBERT in conjunction with conditional random fields to detect entity boundaries precisely.Our framework creates efficient natural language segments by utilizing decoderbased LLMs with 10B parameters.When compared to baseline SecureBERT implementations,evaluation across four cybersecurity data sources shows notable gains,with a 9.4%–25.21%greater recall and a 6.38%–17.3%better F1-score.Our refined model matches larger models and achieves 2.6%–4.9%better F1-score for technical phrase recognition than the state-of-the-art alternatives Claude 3.5 Sonnet,Llama3-8B,and Mixtral-7B.The three-stage architecture identification-extraction-tagging pipeline tackles important cybersecurity NER issues.Through effective architectures,these developments preserve deployability while setting a new standard for entity extraction in challenging security scenarios.The findings show how specific enhancements in hybrid recognition,validation procedures,and prompt engineering raise NER performance above monolithic LLM approaches in cybersecurity applications,especially for technical entity extraction fromheterogeneous sourceswhere conventional techniques fall short.Because of itsmodular nature,the framework can be upgraded at the component level as new methods are developed.展开更多
The photoacoustic imaging of lipid is intrinsically constrained by the feeble nature of endogenous lipid signals,posing a persistent sensitivity challenge that demands innovative solutions.Although adopting high-effic...The photoacoustic imaging of lipid is intrinsically constrained by the feeble nature of endogenous lipid signals,posing a persistent sensitivity challenge that demands innovative solutions.Although adopting high-efficiency excitation and detection elements may improve the imaging sensitivity to a certain extent,the application of the elements is inevitably subject to various limitations in practical applications,particularly during in vivo imaging and endoscopic imaging.In this study,we propose a multi-combinatorial approach to enhance the sensitivity of lipid photoacoustic imaging.The approach involves wavelet transform processing of one-dimensional A-line signals,gradient-based denoising of two-dimensional B-scan images,and finally,threedimensional spatial weighted averaging of the data processed by the previous two steps.This method not only significantly improves the signal-to-noise ratio(SNR)in distinguished feature regions of the image by around 10 dB,but also efficiently extracts weak signals with no distinct features in the original image.After processing with this method,the images acquired under single scanning were compared with those obtained under multiple scanning.The results showed highly consistent image features,with the structural similarity index increasing from 0.2 to 0.8,confirming the accuracy and reliability of the multi-combinatorial approach.展开更多
Visualizing blood flow velocity distribution is essential for comprehending the pathogenesis of various diseases and facilitating early diagnosis and treatment.Current hemodynamic studies utilizing optical coherence t...Visualizing blood flow velocity distribution is essential for comprehending the pathogenesis of various diseases and facilitating early diagnosis and treatment.Current hemodynamic studies utilizing optical coherence tomography(OCT)primarily rely on Doppler OCT(D-OCT)and OCT Angiography(OCTA),which measure axial blood vessel velocity or visualize the vascular architecture,respectively.However,these techniques have limitations in accurately quantifying the absolute velocity of red blood cells(RBCs).This study presents a novel method based on microsphere tracking,which enables precise quantification of absolute blood flow velocity along a blood vessel.In phantom experiments,freshly harvested blood mixed with microspheres was infused into a cellulose tube to simulate a single blood vessel.Experimental results,demon-strating an error margin of less than 10%,validated the effectiveness of this method.Blood flow velocities ranging from 0.472 mm/s to 18.9 mm/s were accurately measured.A preliminary in vivo examination of rabbit ear vessels was conducted,further validating the reliability of this method.This study presents a potential method for specific disease diagnosis by detecting tar-geted vessel flow velocity variations using swept-source optical coherence tomography(SS-OCT)combined with microsphere tracking.展开更多
A new Mg−10%Al−1%Zn−1%Si alloy with non-dendritic microstructure was prepared by strain induced melt activation(SIMA)process.The effect of compression ratio on the evolution of semisolid microstructure of the experime...A new Mg−10%Al−1%Zn−1%Si alloy with non-dendritic microstructure was prepared by strain induced melt activation(SIMA)process.The effect of compression ratio on the evolution of semisolid microstructure of the experimental alloy was investigated.The results indicate that the average size ofα-Mg grains decreases and spheroidizing tendency becomes more obvious with the compression ratios increasing from 0 to 40%.In addition,the eutectic Mg2Si phase in the Mg−10%Al−1%Zn−1%Si alloy transforms completely from the initial fishbone shape to globular shape by SIMA process.With the increasing of compression ratio,the morphology and average size of Mg2Si phases do not change obviously.The morphology modification mechanism of Mg2Si phase in Mg−10%Al−1%Zn−1%Si alloy by SIMA process was also studied.展开更多
Ammonia-oxidizing archaea （AOA） are widely considered key to ammonia oxidation in various environments. However, little work has been conducted to simultaneously investigate the abundance and diversity of AOA as wel...Ammonia-oxidizing archaea （AOA） are widely considered key to ammonia oxidation in various environments. However, little work has been conducted to simultaneously investigate the abundance and diversity of AOA as well as correlations between archaeal amoA genotypes and environmental parameters of different ecosystems at one district. To understand the abundance, diversity, and distribution of AOA in Pearl River Delta of China in response to various habitats, the archaeal amoA genes in soil, marine, river, lake, hot spring and wastewater treatment plant （WWTP） samples were investigated using real-time fluorescent quantitative PCR and clone libraries. Our analyses indicated that the diversity of AOA in various habitats was different and could be clustered into five major clades, i.e., estuary sediment, marine water/sediment, soil, hot spring and Cluster 1. Phylogenetic analyses revealed that the structure of AOA communities in similar ecological habitats exhibited strong relation. The canonical correspondence method indicated that the AOA community structure was strongly correlated to temperature, pH, total organic carbon, total nitrogen and dissolved oxygen variables. Assessing AOA amoA gene copy numbers, ranging from 6.84× 10^6 to 9.45 × 10^7 copies/g in dry soil/sediment, and 6.06× 10^6 to 2.41 ×10^7 copies/L in water samples, were higher than ammonia-oxidizing bacteria （AOB） by 1-2 orders of magnitude. However, AOA amoA copy numbers were much lower than AOB in WWTP activated sludge samples. Overall, these studies suggested that AOA may be a major contributor to ammonia oxidation in natural habitats but play a minor role in highly aerated activated sludge. The result also showed the ratio of AOA to AOB amoA gene abundance was positively correlated with temperature and less correlated with other environmental parameters. New data from our study provide increasing evidence for the relative abundance and diversity of ammonia-oxidizing archaea in the global nitrogen cycle.展开更多
Digestive tract tumors acount for 15%and 19.3%of the cancer incidence and deaths,respec-tively.Early detection of digestive tract tumors is crucial to the reduction of global cancer burden.Two-photon excitation fuores...Digestive tract tumors acount for 15%and 19.3%of the cancer incidence and deaths,respec-tively.Early detection of digestive tract tumors is crucial to the reduction of global cancer burden.Two-photon excitation fuorescence lifetime imaging microscopy(TP-FLIM)allows non-invasive,label free,three-dimensional,high-resolution imaging of living tisues with not only histological but also biochemical characterization ability in both qualitative and quantitative way.Benefiting from these advantages,this technology is protmising for clinical diagnosis of digestive tract tumors.In recent years,many efforts have'been made in this field and some remarkable progress has been achieved.In this paper,we overview the recent progress of TP-FLIM-based researches on digestive tract tumor detection.Among them,our latest results on the gastric cancer and esophageal cancer are elaborately depicted.Finally,we outlook and discuss the potential advantages and challenges of TP-FLIM in future clinical applications.展开更多
Platinum is generally known as the most effective electrocatalyst for hydrogen evolution reaction because it can greatly lower the overpotential and accelerate the reaction kinetics,while its commercial potential alwa...Platinum is generally known as the most effective electrocatalyst for hydrogen evolution reaction because it can greatly lower the overpotential and accelerate the reaction kinetics,while its commercial potential always suffers from scarcity,high cost,low utilization,and poor durability particularly in acidic electrolytes.We herein demonstrate a facile method to improve the hydrogen evolution performance of Pt-based electrocatalysts by simply decorating the-state-of-the-art and commercially available Pt/C with hydrophobic protic([DBU][NTf2])or aprotic([BMIm][NTf2])ionic liquid.The current densities of[BMIm]@Pt/C and[DBU-H]@Pt/C with 10% ionic liquid at an overpotential of 40 mV are 2.81 and 4.15 times,respectively,higher than that of the pristine Pt/C.More importantly,ionic liquid-decoration significantly improves the long-term stability of Pt nanoparticles.After 8 h of chronoamperometric measurements,[DBU-H]@Pt/C and[BMIm]@Pt/C can still retain 83.7% and 78.3% of their original activity,respectively,which is much higher than that of the pristine Pt/C(24.4%).The improved performance of Pt/C decorated with ionic liquid is considered to arise from the improved proton conductivity(particularly for protic ionic liquid)and hydrophobic microenvironment created by the supported ionic liquid phase.The presence of ionic liquid layer not only de-coordinates H+from hydronium ions nearby the Pt nanoparticles,but it also protects Pt nanoparticles from dissolution in the acidic media.展开更多
Optical-resolution photoacoustic microscopy(OR-PAM)has been shown to be an excellent tool for high-resolution imaging of microvasculature,and quantitative analysis of the microvascula-ture can provide valuable informa...Optical-resolution photoacoustic microscopy(OR-PAM)has been shown to be an excellent tool for high-resolution imaging of microvasculature,and quantitative analysis of the microvascula-ture can provide valuable information for the early diagnosis and treatment of various vascular-related diseases.In order to address the characteristics of weak signals,discontinuity and small diameters in photoacoustic microvascular images,we propose a method adaptive to the micro-vascular segmentation in photoacoustic images,including Hessian matrix enhancement and the morphological connection operators.The accuracy of our vascular segmentation method is quantitatively evaluated by the multiple criteria.To obtain more precise and continuous mi-crovascular skeletons,an improved skeleton extraction framework based on the multistencil fast marching(MSFM)method is developed.We carried out in vivo OR-PAM microvascular imaging in mouse ears and subcutaneous hepatoma tumor model to verify the correctness and superiority of our proposed method.Compared with the previous methods,our proposed method can extract the microvascular network more completely,continuously and accurately,and provide an ef-fective solution for the quantitative analysis of photoacoustic microvascular images with many small branches.展开更多
Terahertz technology is continually evolving and much progress has been made in recent years.Many new applications are being discovered and new ways to implement terahertz imaging investigated.In this review,we limit ...Terahertz technology is continually evolving and much progress has been made in recent years.Many new applications are being discovered and new ways to implement terahertz imaging investigated.In this review,we limit our discussion to biomedical applications of terahertz imaging such as cancer detection,genetic sensing and molecular spectroscopy.Our discussion of the development of new terahertz techniques is also focused on those that may accelerate the progress of terahertz imaging and spectroscopy in biomedicine.展开更多
Mg-6Zn-2X(Fe/Cu/Ni)alloys were prepared through semi-continuous casting,with the aim of identifying a degradable magnesium(Mg)alloy suitable for use in fracturing balls.A comparative analysis was conducted to assess t...Mg-6Zn-2X(Fe/Cu/Ni)alloys were prepared through semi-continuous casting,with the aim of identifying a degradable magnesium(Mg)alloy suitable for use in fracturing balls.A comparative analysis was conducted to assess the impacts of adding Cu and Ni,which result in finer grains and the formation of galvanic corrosion sites.Scanner electronic microscopy examination revealed that precipitated phases concentrated at grain boundaries,forming a semi-continuous network structure that facilitated corrosion penetration in Mg-6Zn-2Cu and Mg-6Zn-2Ni alloys.Pitting corrosion was observed in Mg-6Zn-2Fe,while galvanic corrosion was identified as the primary mechanism in Mg-6Zn-2Cu and Mg-6Zn-2Ni alloys.Among the tests,the Mg-6Zn-2Ni alloy exhibited the highest corrosion rate(approximately 932.9 mm/a)due to its significant potential difference.Mechanical testing showed that Mg-6Zn-2Ni alloy possessed suitable ultimate compressive strength,making it a potential candidate material for degradable fracturing balls,effectively addressing the challenges of balancing strength and degradation rate in fracturing applications.展开更多
1 Introduction Recurrent pregnant loss,gestational diabetes,premature delivery,intrauterine growth restriction,preeclampsia and other pregnancy-related complications have severe impact on the fetus development and the...1 Introduction Recurrent pregnant loss,gestational diabetes,premature delivery,intrauterine growth restriction,preeclampsia and other pregnancy-related complications have severe impact on the fetus development and the health and life quality of the mother.These diseases are also causes of unstability and huge economic burden for the family as well as展开更多
For the reliability and power consumption issues of Ethernet data transmission based on the field programmable gate array （FPGA）, a low-power consumption design method is proposed, which is suitable for FPGA impleme...For the reliability and power consumption issues of Ethernet data transmission based on the field programmable gate array （FPGA）, a low-power consumption design method is proposed, which is suitable for FPGA implementation. To reduce the dynamic power consumption of integrated circuit （IC） design, the proposed method adopts the dynamic control of the clock frequency. For most of the time, when the port is in the idle state or lower-rate state, users can reduce or even turn off the reading clock frequency and reduce the clock flip frequency in order to reduce the dynamic power consumption. When the receiving rate is high, the reading clock frequency will be improved timely to ensure that no data will lost. Simulated and verified by Modelsim, the proposed method can dynamically control the clock frequency, including the dynamic switching of high-speed and low-speed clock flip rates, or stop of the clock flip.展开更多
[Objective]To find out the situation of Nansha Coast Park point and non-point source pollution.[Method]By investigating the park water environment,analysis of point and non-point source pollutants contribution rate,se...[Objective]To find out the situation of Nansha Coast Park point and non-point source pollution.[Method]By investigating the park water environment,analysis of point and non-point source pollutants contribution rate,setting up water quality monitoring sites for basic data related indicators and then using national water quality standards to evaluate water quality.[Result]The Coast Park point source pollution mainly comes from the campus greeting fertilizer spraying.The COD of lakes and river outside the park and ammonia mean concentration belong to grade III.The total nitrogen of lake belongs to grade III.The total phosphorus belongs to grade IV.The total nitrogen of river is the worst.The total phosphorus is grade V.[Conclusion] The lake water quality is highly affected by the point and non-point source pollution,the quality of the river is worse than that of the lake in the park,and it needs powerful governance.展开更多
This study explores the potential of Artificial Intelligence(AI)in early screening and prognosis of Dry Eye Disease(DED),aiming to enhance the accuracy of therapeutic approaches for eye-care practitioners.Despite the ...This study explores the potential of Artificial Intelligence(AI)in early screening and prognosis of Dry Eye Disease(DED),aiming to enhance the accuracy of therapeutic approaches for eye-care practitioners.Despite the promising opportunities,challenges such as diverse diagnostic evidence,complex etiology,and interdisciplinary knowledge integration impede the interpretability,reliability,and applicability of AI-based DED detection methods.The research conducts a comprehensive review of datasets,diagnostic evidence,and standards,as well as advanced algorithms in AI-based DED detection over the past five years.The DED diagnostic methods are categorized into three groups based on their relationship with AI techniques:(1)those with ground truth and/or comparable standards,(2)potential AI-based methods with significant advantages,and(3)supplementary methods for AI-based DED detection.The study proposes suggested DED detection standards,the combination of multiple diagnostic evidence,and future research directions to guide further investigations.Ultimately,the research contributes to the advancement of ophthalmic disease detection by providing insights into knowledge foundations,advanced methods,challenges,and potential future perspectives,emphasizing the significant role of AI in both academic and practical aspects of ophthalmology.展开更多
Power backup infrastructure is indispensable but its cost exceeds 20%of the whole power infrastructure expenditure of a traditional datacenter.Under-provisioning the power backup infrastructure has therefore been prop...Power backup infrastructure is indispensable but its cost exceeds 20%of the whole power infrastructure expenditure of a traditional datacenter.Under-provisioning the power backup infrastructure has therefore been proposed to reduce the backup cost while still keep power available during grid power outages.However,how to under-provision the power backup facility for a green datacenter using renewable energy has not yet been explored.This paper proposes an approach to under-provision the power backup infrastructure as well as optimize the performance of individual applications with the presence of renewable energy,named Green-Up.It contributes two novel techniques:power source and power load managements.Power source management identifies the suitable power source for power backup whereas power load management selects the best power capping techniques for under-provisioning power backup infrastructure.In addition,we build hierarchical Bayesian Models to optimize power consumption and performance.To evaluate Green-Up,we build an experimental cluster consisting of 10 servers with a simulated solar power generator,and use four representative datacenter benchmarks.The experimental results demonstrate that our theoretical solutions provide a seamless bridge across the whole spectrum of renewable power availability and durations of grid power outages.展开更多
Defects at the buried interface are the primary factors contributing to recombination losses and instability in perovskite solar cells(PSCs)with n-i-p structure.Here,a molecule with bilateral electron-donating groups,...Defects at the buried interface are the primary factors contributing to recombination losses and instability in perovskite solar cells(PSCs)with n-i-p structure.Here,a molecule with bilateral electron-donating groups,6-amino-1-hexanol(HAL),is introduced between SnO_(2)and perovskite(PVK)to optimize the characteristics of the buried interfacial properties,as well as the PVK film quality.The surface defects of SnO_(2)can be more effectively passivated,and its energy level structure can be tuned more appropriately.展开更多
Background:The advent of mobile health(mHealth)applications has fundamentally transformed the healthcare landscape,particularly within the field of ophthalmology,by providing unprecedented opportunities for remote dia...Background:The advent of mobile health(mHealth)applications has fundamentally transformed the healthcare landscape,particularly within the field of ophthalmology,by providing unprecedented opportunities for remote diagnosis,monitoring,and treatment.Ocular surface diseases,including dry eye disease(DED),are the most common eye diseases that can be detected by mHealth applications.However,most remote artificial intelligence(AI)systems for ocular surface disease detection are predominantly based on self-reported data collected through interviews,which lack the rigor of clinical evidence.These constraints underscore the need to develop robust,evidence-based AI frameworks that incorporate objective health indicators to improve the reliability and clinical utility of remote health applications.Methods:Two novel deep learning(DL)models,YoloTR and YoloMBTR,were developed to detect key ocular surface indicators(OSIs),including tear meniscus height(TMH),non-invasive Keratograph break-up time(NIKBUT),ocular redness,lipid layer,and trichiasis.Additionally,back propagation neural networks(BPNN)and universal network for image segmentation(U-Net)were employed for image classification and segmentation of meibomian gland images to predict Demodex mite infections.These models were trained on a large dataset from high-resolution devices,including Keratograph 5M and various mobile platforms(Huawei,Apple,and Xiaomi).Results:The proposed DL models of YoloMBTR and YoloTR outperformed baseline you only look once(YOLO)models(Yolov5n,Yolov6n,and Yolov8n)across multiple performance metrics,including test average precision(AP),validation AP,and overall accuracy.These two models also exhibit superior performance compared to machine plug-in models in KG5M when benchmarked against the gold standard.Using Python's Matplotlib for visualization and SPSS for statistical analysis,this study introduces an innovative proof-of-concept framework leveraging quantitative AI analysis to address critical challenges in ophthalmology.By integrating advanced DL models,the framework offers a robust approach for detecting and quantifying OSIs with a high degree of precision.This methodological advancement bridges the gap between AI-driven diagnostics and clinical ophthalmology by translating complex ocular data into actionable insights.Conclusions:Integrating AI with clinical laboratory data holds significant potential for advancing mobile eye health(MeHealth),particularly in detecting OSIs.This study aims to explore this integration,focusing on improving diagnostic accuracy and accessibility.This study demonstrates the potential of AI-driven tools in ophthalmic diagnostics,paving the way for reliable,evidence-based solutions in remote patient monitoring and continuous care.The results contribute to the foundation of AI-powered health systems that can extend beyond ophthalmology,improving healthcare accessibility and patient outcomes across various domains.展开更多
A convective assembly technique at the micron scale analogous to the writing action of a ＂pipette pen＂ has been developed for the linear assembly of gold nanoparticle strips with micron scale width and millimeter sc...A convective assembly technique at the micron scale analogous to the writing action of a ＂pipette pen＂ has been developed for the linear assembly of gold nanoparticle strips with micron scale width and millimeter scale length for surface enhanced Raman scattering （SERS）. The arrays with interparticle gaps smaller than 3 nm are hexagonally stacked in the vicinity of the pipette tip. Variable numbers of stacked layers and clean surfaces of the assembled nanoparticles are obtained by optimizing the velocity of the pipette tip. The SERS properties of tile assembled nanoparticle arrays rely on their stacking number and surface cleanliness.展开更多
Nowadays,it is a matter of great concern to design electrode materials with excellent electrochemical performance for supercapacitors by a safe,efficient and simple method.And these characteristics are usually related...Nowadays,it is a matter of great concern to design electrode materials with excellent electrochemical performance for supercapacitors by a safe,efficient and simple method.And these characteristics are usually related to the vacancies and impurities in the electrode.To investigate the effect of the vacancies on the electrochemical properties of the supercapacitor cathode material,the uniform reduced CoNi2S4(r-CoNi2S4)nanosheets with sulfur vacancies have been successfully prepared by a one-step hydrothermal method.And the formation of sulfur vacancies are characterized by Raman,X-ray photoelectron spectroscopy and other means.As the electrode for supercapacitor,the r-CoNi2S4 nanosheet electrode delivers a high capacity of 1918.9 Fg-1 at a current density of 1 A g-1,superior rate capability(87.9%retention at a current density of 20 A g-1)and extraordinary cycling stability.Compared with the original CoNi2S4 nanosheet electrode(1226 F g-1at current density of 1 A g-1),the r-CoNi2S4 nanosheet electrode shows a great improvement.The asymmetric supercapacitor based on the r-CoNi2S4 positive electrode and activated carbon negative electrode exhibits a high energy density of 30.3 Wh kg-1 at a power density of 802.1 W kg-1,as well as excellent long-term cycling stability.The feasibility and great potential of the device in practical applications have been successfully proved by lightening the light emitting diodes of three different colors.展开更多
It is crucial to discover lead-free materials with ultrahigh recoverable energy density(Wrec)that can be employed in future pulse power capacitors.In this work,a high Wrec of 4.51 J/cm^(3) was successfully obtained in...It is crucial to discover lead-free materials with ultrahigh recoverable energy density(Wrec)that can be employed in future pulse power capacitors.In this work,a high Wrec of 4.51 J/cm^(3) was successfully obtained in lead-free Nd-doped AgNb_(0.8)Ta_(0.2)O_(3) antiferroelectric ceramics at an applied electric field of 290 kV/cm.It is discovered that Nd doping paired with Nb-site vacancies could stabilize the antiferroelectric phase by lowering the temperatures of the M1-M2 and M2-M3 phase transitions,which leads to higher energy storage efficiency.Furthermore,Nd and Ta co-doping will contribute to the electrical homogeneity and low electrical conductivity,resulting in large breakdown strengths.Aliovalent doping in Ag-site with Nb-site vacancies serves as a novel strategy for the construction of AgNbO_(3)-based ceramics with excellent energy storage performance.展开更多
文摘Although Named Entity Recognition(NER)in cybersecurity has historically concentrated on threat intelligence,vital security data can be found in a variety of sources,such as open-source intelligence and unprocessed tool outputs.When dealing with technical language,the coexistence of structured and unstructured data poses serious issues for traditional BERT-based techniques.We introduce a three-phase approach for improved NER inmulti-source cybersecurity data that makes use of large language models(LLMs).To ensure thorough entity coverage,our method starts with an identification module that uses dynamic prompting techniques.To lessen hallucinations,the extraction module uses confidence-based self-assessment and cross-checking using regex validation.The tagging module links to knowledge bases for contextual validation and uses SecureBERT in conjunction with conditional random fields to detect entity boundaries precisely.Our framework creates efficient natural language segments by utilizing decoderbased LLMs with 10B parameters.When compared to baseline SecureBERT implementations,evaluation across four cybersecurity data sources shows notable gains,with a 9.4%–25.21%greater recall and a 6.38%–17.3%better F1-score.Our refined model matches larger models and achieves 2.6%–4.9%better F1-score for technical phrase recognition than the state-of-the-art alternatives Claude 3.5 Sonnet,Llama3-8B,and Mixtral-7B.The three-stage architecture identification-extraction-tagging pipeline tackles important cybersecurity NER issues.Through effective architectures,these developments preserve deployability while setting a new standard for entity extraction in challenging security scenarios.The findings show how specific enhancements in hybrid recognition,validation procedures,and prompt engineering raise NER performance above monolithic LLM approaches in cybersecurity applications,especially for technical entity extraction fromheterogeneous sourceswhere conventional techniques fall short.Because of itsmodular nature,the framework can be upgraded at the component level as new methods are developed.
基金supported by the National Key Research and Development Program of China(2022YFC2402400)the National Natural Science Foundation of China(82027803,62275062)+7 种基金the Guangdong Provincial Key Laboratory of Biomedical Optical Imaging Technology(2020B121201010)the Shenzhen Science and Technology Innovation Committee under Grant(JCYJ20220818101417039)the Shenzhen Key Laboratory for Molecular lmaging(ZDSY20130401165820357)the Shenzhen Medical Research Fund(D2404002)the Project of Shandong Innovation and Startup Community of High-end Medical Apparatus and Instruments(2023-SGTTXM-002 and 2024-SGTTXM-005)the Shandong Province Technology Innovation Guidance Plan(Central Leading Local Science and Technology Development Fund)(YDZX2023115)the Taishan Scholar Special Funding Project of Shandong Provinceand the Shandong Laboratory of Advanced Biomaterials and Medical Devices in Weihai(ZL202402).
文摘The photoacoustic imaging of lipid is intrinsically constrained by the feeble nature of endogenous lipid signals,posing a persistent sensitivity challenge that demands innovative solutions.Although adopting high-efficiency excitation and detection elements may improve the imaging sensitivity to a certain extent,the application of the elements is inevitably subject to various limitations in practical applications,particularly during in vivo imaging and endoscopic imaging.In this study,we propose a multi-combinatorial approach to enhance the sensitivity of lipid photoacoustic imaging.The approach involves wavelet transform processing of one-dimensional A-line signals,gradient-based denoising of two-dimensional B-scan images,and finally,threedimensional spatial weighted averaging of the data processed by the previous two steps.This method not only significantly improves the signal-to-noise ratio(SNR)in distinguished feature regions of the image by around 10 dB,but also efficiently extracts weak signals with no distinct features in the original image.After processing with this method,the images acquired under single scanning were compared with those obtained under multiple scanning.The results showed highly consistent image features,with the structural similarity index increasing from 0.2 to 0.8,confirming the accuracy and reliability of the multi-combinatorial approach.
基金supported by the National Natural Science Foundation of China(62175156,81827807)the Science and Technology Commission of Shanghai Municipality(22S31903000)+3 种基金the Collaborative Innovation Project of Shanghai Institute of Technology(XTCX2022-27)the Shenzhen Basic Research Key Project(JCYJ20220818103212026)the Shenzhen Key Technology Project(JSGGZD20220822095200002)the Shenzhen Outstanding Scientific and Technological Innovation Talents Distinguished Young Scientists(RCJC20210609104443085).
文摘Visualizing blood flow velocity distribution is essential for comprehending the pathogenesis of various diseases and facilitating early diagnosis and treatment.Current hemodynamic studies utilizing optical coherence tomography(OCT)primarily rely on Doppler OCT(D-OCT)and OCT Angiography(OCTA),which measure axial blood vessel velocity or visualize the vascular architecture,respectively.However,these techniques have limitations in accurately quantifying the absolute velocity of red blood cells(RBCs).This study presents a novel method based on microsphere tracking,which enables precise quantification of absolute blood flow velocity along a blood vessel.In phantom experiments,freshly harvested blood mixed with microspheres was infused into a cellulose tube to simulate a single blood vessel.Experimental results,demon-strating an error margin of less than 10%,validated the effectiveness of this method.Blood flow velocities ranging from 0.472 mm/s to 18.9 mm/s were accurately measured.A preliminary in vivo examination of rabbit ear vessels was conducted,further validating the reliability of this method.This study presents a potential method for specific disease diagnosis by detecting tar-geted vessel flow velocity variations using swept-source optical coherence tomography(SS-OCT)combined with microsphere tracking.
基金The authors are grateful for the financial supports from the National Natural Science Foundation of China(Nos.41807235,50674038).
文摘A new Mg−10%Al−1%Zn−1%Si alloy with non-dendritic microstructure was prepared by strain induced melt activation(SIMA)process.The effect of compression ratio on the evolution of semisolid microstructure of the experimental alloy was investigated.The results indicate that the average size ofα-Mg grains decreases and spheroidizing tendency becomes more obvious with the compression ratios increasing from 0 to 40%.In addition,the eutectic Mg2Si phase in the Mg−10%Al−1%Zn−1%Si alloy transforms completely from the initial fishbone shape to globular shape by SIMA process.With the increasing of compression ratio,the morphology and average size of Mg2Si phases do not change obviously.The morphology modification mechanism of Mg2Si phase in Mg−10%Al−1%Zn−1%Si alloy by SIMA process was also studied.
基金supported by the National Natural Science Foundation of China (No. 50978069)
文摘Ammonia-oxidizing archaea （AOA） are widely considered key to ammonia oxidation in various environments. However, little work has been conducted to simultaneously investigate the abundance and diversity of AOA as well as correlations between archaeal amoA genotypes and environmental parameters of different ecosystems at one district. To understand the abundance, diversity, and distribution of AOA in Pearl River Delta of China in response to various habitats, the archaeal amoA genes in soil, marine, river, lake, hot spring and wastewater treatment plant （WWTP） samples were investigated using real-time fluorescent quantitative PCR and clone libraries. Our analyses indicated that the diversity of AOA in various habitats was different and could be clustered into five major clades, i.e., estuary sediment, marine water/sediment, soil, hot spring and Cluster 1. Phylogenetic analyses revealed that the structure of AOA communities in similar ecological habitats exhibited strong relation. The canonical correspondence method indicated that the AOA community structure was strongly correlated to temperature, pH, total organic carbon, total nitrogen and dissolved oxygen variables. Assessing AOA amoA gene copy numbers, ranging from 6.84× 10^6 to 9.45 × 10^7 copies/g in dry soil/sediment, and 6.06× 10^6 to 2.41 ×10^7 copies/L in water samples, were higher than ammonia-oxidizing bacteria （AOB） by 1-2 orders of magnitude. However, AOA amoA copy numbers were much lower than AOB in WWTP activated sludge samples. Overall, these studies suggested that AOA may be a major contributor to ammonia oxidation in natural habitats but play a minor role in highly aerated activated sludge. The result also showed the ratio of AOA to AOB amoA gene abundance was positively correlated with temperature and less correlated with other environmental parameters. New data from our study provide increasing evidence for the relative abundance and diversity of ammonia-oxidizing archaea in the global nitrogen cycle.
基金supports from the National Key Research and Development Program of China(2017YFC0110200)Program 973(2015CB755502)+4 种基金the National Natural Science Foundation of China(NSFC)(81571724,81701744,81822023)the Natural Science Foundation of Guangdong Province(2014A030312006,2017A 030310308)the Scientific Instrument Innovation Team of Chinese Academy of Sciences(GJJSTD 20180002)the Shenzhen Science and Technology Program(JCYJ20170818164343304,JCYJ20170818155006471,JCYJ20160608214524052,JCYJ20180507182432303)the SIAT Innovation Program for Excellent Young Researchers(201821).
文摘Digestive tract tumors acount for 15%and 19.3%of the cancer incidence and deaths,respec-tively.Early detection of digestive tract tumors is crucial to the reduction of global cancer burden.Two-photon excitation fuorescence lifetime imaging microscopy(TP-FLIM)allows non-invasive,label free,three-dimensional,high-resolution imaging of living tisues with not only histological but also biochemical characterization ability in both qualitative and quantitative way.Benefiting from these advantages,this technology is protmising for clinical diagnosis of digestive tract tumors.In recent years,many efforts have'been made in this field and some remarkable progress has been achieved.In this paper,we overview the recent progress of TP-FLIM-based researches on digestive tract tumor detection.Among them,our latest results on the gastric cancer and esophageal cancer are elaborately depicted.Finally,we outlook and discuss the potential advantages and challenges of TP-FLIM in future clinical applications.
基金supported by the National Natural Science Foundation of China(Grant Nos.51772089,21872046 and 21805304)the Youth 1000 Talent Program of China+4 种基金the Outstanding Youth Scientist Foundation of Hunan Province(Grant No.2018JJ1009)Provincial Science and Technology Innovation PlatformTalent Plan-Changsha,Zhuzhou and Xiangtan High-level Talents Accumulation Project(Grant No.2017XK2023)the Youth Scientist Foundation of Hunan Province(Grant No.S2019JJQNJJ0628)the Research and Development Plan of Key Areas in Hunan Province(Grant No.2019GK2235)。
文摘Platinum is generally known as the most effective electrocatalyst for hydrogen evolution reaction because it can greatly lower the overpotential and accelerate the reaction kinetics,while its commercial potential always suffers from scarcity,high cost,low utilization,and poor durability particularly in acidic electrolytes.We herein demonstrate a facile method to improve the hydrogen evolution performance of Pt-based electrocatalysts by simply decorating the-state-of-the-art and commercially available Pt/C with hydrophobic protic([DBU][NTf2])or aprotic([BMIm][NTf2])ionic liquid.The current densities of[BMIm]@Pt/C and[DBU-H]@Pt/C with 10% ionic liquid at an overpotential of 40 mV are 2.81 and 4.15 times,respectively,higher than that of the pristine Pt/C.More importantly,ionic liquid-decoration significantly improves the long-term stability of Pt nanoparticles.After 8 h of chronoamperometric measurements,[DBU-H]@Pt/C and[BMIm]@Pt/C can still retain 83.7% and 78.3% of their original activity,respectively,which is much higher than that of the pristine Pt/C(24.4%).The improved performance of Pt/C decorated with ionic liquid is considered to arise from the improved proton conductivity(particularly for protic ionic liquid)and hydrophobic microenvironment created by the supported ionic liquid phase.The presence of ionic liquid layer not only de-coordinates H+from hydronium ions nearby the Pt nanoparticles,but it also protects Pt nanoparticles from dissolution in the acidic media.
基金supported in part by the National Natural Science Foundation of China Grants[Nos.91739117 and 61701279]
文摘Optical-resolution photoacoustic microscopy(OR-PAM)has been shown to be an excellent tool for high-resolution imaging of microvasculature,and quantitative analysis of the microvascula-ture can provide valuable information for the early diagnosis and treatment of various vascular-related diseases.In order to address the characteristics of weak signals,discontinuity and small diameters in photoacoustic microvascular images,we propose a method adaptive to the micro-vascular segmentation in photoacoustic images,including Hessian matrix enhancement and the morphological connection operators.The accuracy of our vascular segmentation method is quantitatively evaluated by the multiple criteria.To obtain more precise and continuous mi-crovascular skeletons,an improved skeleton extraction framework based on the multistencil fast marching(MSFM)method is developed.We carried out in vivo OR-PAM microvascular imaging in mouse ears and subcutaneous hepatoma tumor model to verify the correctness and superiority of our proposed method.Compared with the previous methods,our proposed method can extract the microvascular network more completely,continuously and accurately,and provide an ef-fective solution for the quantitative analysis of photoacoustic microvascular images with many small branches.
文摘Terahertz technology is continually evolving and much progress has been made in recent years.Many new applications are being discovered and new ways to implement terahertz imaging investigated.In this review,we limit our discussion to biomedical applications of terahertz imaging such as cancer detection,genetic sensing and molecular spectroscopy.Our discussion of the development of new terahertz techniques is also focused on those that may accelerate the progress of terahertz imaging and spectroscopy in biomedicine.
基金financially supported by the Key Scientific Research Project in Shanxi Province,China(No.202102050201003)the National Natural Science Foundation of China(No.52071227)+2 种基金the Natural Science Foundation of Shanxi Province,China(No.202103021223293)the Central Guiding Science and Technology Development of Local Fund,China(No.YDZJSK20231A046)the Postgraduate Education Innovation Project of Shanxi Province,China(No.2023Y686)。
文摘Mg-6Zn-2X(Fe/Cu/Ni)alloys were prepared through semi-continuous casting,with the aim of identifying a degradable magnesium(Mg)alloy suitable for use in fracturing balls.A comparative analysis was conducted to assess the impacts of adding Cu and Ni,which result in finer grains and the formation of galvanic corrosion sites.Scanner electronic microscopy examination revealed that precipitated phases concentrated at grain boundaries,forming a semi-continuous network structure that facilitated corrosion penetration in Mg-6Zn-2Cu and Mg-6Zn-2Ni alloys.Pitting corrosion was observed in Mg-6Zn-2Fe,while galvanic corrosion was identified as the primary mechanism in Mg-6Zn-2Cu and Mg-6Zn-2Ni alloys.Among the tests,the Mg-6Zn-2Ni alloy exhibited the highest corrosion rate(approximately 932.9 mm/a)due to its significant potential difference.Mechanical testing showed that Mg-6Zn-2Ni alloy possessed suitable ultimate compressive strength,making it a potential candidate material for degradable fracturing balls,effectively addressing the challenges of balancing strength and degradation rate in fracturing applications.
基金supported by grants from Natural Science Foundation of Guangdong Province(S2013010012847)National Basic Research Program of China(2013CB945503)Fundamental Research Project of Shenzhen(JCYJ20120615130350920)
文摘1 Introduction Recurrent pregnant loss,gestational diabetes,premature delivery,intrauterine growth restriction,preeclampsia and other pregnancy-related complications have severe impact on the fetus development and the health and life quality of the mother.These diseases are also causes of unstability and huge economic burden for the family as well as
基金supported by the Natural Science Foundation of China under Grant No.61376024 and No.61306024Natural Science Foundation of Guangdong Province under Grant No.S2013040014366Basic Research Programme of Shenzhen under Grant No.JCYJ20140417113430642 and No.JCYJ20140901003939020
文摘For the reliability and power consumption issues of Ethernet data transmission based on the field programmable gate array （FPGA）, a low-power consumption design method is proposed, which is suitable for FPGA implementation. To reduce the dynamic power consumption of integrated circuit （IC） design, the proposed method adopts the dynamic control of the clock frequency. For most of the time, when the port is in the idle state or lower-rate state, users can reduce or even turn off the reading clock frequency and reduce the clock flip frequency in order to reduce the dynamic power consumption. When the receiving rate is high, the reading clock frequency will be improved timely to ensure that no data will lost. Simulated and verified by Modelsim, the proposed method can dynamically control the clock frequency, including the dynamic switching of high-speed and low-speed clock flip rates, or stop of the clock flip.
基金Supported by Open Course by National Key Lab of Fresh Water Ecology and Biological Technology(2012-FB12)Major Breakthrough in Key Areas in Guangdong and Hongkong(2012A090200001)
文摘[Objective]To find out the situation of Nansha Coast Park point and non-point source pollution.[Method]By investigating the park water environment,analysis of point and non-point source pollutants contribution rate,setting up water quality monitoring sites for basic data related indicators and then using national water quality standards to evaluate water quality.[Result]The Coast Park point source pollution mainly comes from the campus greeting fertilizer spraying.The COD of lakes and river outside the park and ammonia mean concentration belong to grade III.The total nitrogen of lake belongs to grade III.The total phosphorus belongs to grade IV.The total nitrogen of river is the worst.The total phosphorus is grade V.[Conclusion] The lake water quality is highly affected by the point and non-point source pollution,the quality of the river is worse than that of the lake in the park,and it needs powerful governance.
基金funded by the National Natural Science Foundation of China Natural(Nos.U22A2041,82071915,and 62372047)the Shenzhen Key Laboratory of Intelligent Bioinformatics(No.ZDSYS20220422103800001)+5 种基金the Shenzhen Science and Technology Program(No.KQTD20200820113106007)the Guangdong Basic and Applied Basic Research Foundation(No.2022A1515220015)the Zhuhai Technology and Research Foundation(Nos.ZH22036201210034PWC,2220004000131,and 2220004002412)the Project of Humanities and Social Science of MOE(Ministry of Education in China)(No.22YJCZH213)the Science and Technology Research Program of Chongqing Municipal Education Commission(Nos.KJZD-K202203601,KJQN0202203605,and KJQN202203607)the Natural Science Foundation of Chongqing China(No.cstc2021jcyj-msxmX1108).
文摘This study explores the potential of Artificial Intelligence(AI)in early screening and prognosis of Dry Eye Disease(DED),aiming to enhance the accuracy of therapeutic approaches for eye-care practitioners.Despite the promising opportunities,challenges such as diverse diagnostic evidence,complex etiology,and interdisciplinary knowledge integration impede the interpretability,reliability,and applicability of AI-based DED detection methods.The research conducts a comprehensive review of datasets,diagnostic evidence,and standards,as well as advanced algorithms in AI-based DED detection over the past five years.The DED diagnostic methods are categorized into three groups based on their relationship with AI techniques:(1)those with ground truth and/or comparable standards,(2)potential AI-based methods with significant advantages,and(3)supplementary methods for AI-based DED detection.The study proposes suggested DED detection standards,the combination of multiple diagnostic evidence,and future research directions to guide further investigations.Ultimately,the research contributes to the advancement of ophthalmic disease detection by providing insights into knowledge foundations,advanced methods,challenges,and potential future perspectives,emphasizing the significant role of AI in both academic and practical aspects of ophthalmology.
文摘Power backup infrastructure is indispensable but its cost exceeds 20%of the whole power infrastructure expenditure of a traditional datacenter.Under-provisioning the power backup infrastructure has therefore been proposed to reduce the backup cost while still keep power available during grid power outages.However,how to under-provision the power backup facility for a green datacenter using renewable energy has not yet been explored.This paper proposes an approach to under-provision the power backup infrastructure as well as optimize the performance of individual applications with the presence of renewable energy,named Green-Up.It contributes two novel techniques:power source and power load managements.Power source management identifies the suitable power source for power backup whereas power load management selects the best power capping techniques for under-provisioning power backup infrastructure.In addition,we build hierarchical Bayesian Models to optimize power consumption and performance.To evaluate Green-Up,we build an experimental cluster consisting of 10 servers with a simulated solar power generator,and use four representative datacenter benchmarks.The experimental results demonstrate that our theoretical solutions provide a seamless bridge across the whole spectrum of renewable power availability and durations of grid power outages.
基金supported by the project of the National Natural Science Foundation of China(No.22271106,51972123,61804058,U20A20150,and U1705256)Young Elite Scientist Sponsorship Program by Cast of China Association for Science and Technology(YESS20210285)Guangdong Basic and Applied Basic Research Foundation(2022A1515011613).
文摘Defects at the buried interface are the primary factors contributing to recombination losses and instability in perovskite solar cells(PSCs)with n-i-p structure.Here,a molecule with bilateral electron-donating groups,6-amino-1-hexanol(HAL),is introduced between SnO_(2)and perovskite(PVK)to optimize the characteristics of the buried interfacial properties,as well as the PVK film quality.The surface defects of SnO_(2)can be more effectively passivated,and its energy level structure can be tuned more appropriately.
基金funded by the National Natural Science Foundation of China(Grant/Award Numbers:U22A2041,62372047)Shenzhen Key Laboratory of Intelligent Bioinformatics(Grant/Award Number:ZDSYS20220422103800001)+1 种基金Shenzhen Science and Technology Program(Grant/Award Number:KQTD20200820113106007)the Characteristic Innovation Project of Ordinary Universities in Guangdong Province(Grant/Award Number:2024KTSCX226).
文摘Background:The advent of mobile health(mHealth)applications has fundamentally transformed the healthcare landscape,particularly within the field of ophthalmology,by providing unprecedented opportunities for remote diagnosis,monitoring,and treatment.Ocular surface diseases,including dry eye disease(DED),are the most common eye diseases that can be detected by mHealth applications.However,most remote artificial intelligence(AI)systems for ocular surface disease detection are predominantly based on self-reported data collected through interviews,which lack the rigor of clinical evidence.These constraints underscore the need to develop robust,evidence-based AI frameworks that incorporate objective health indicators to improve the reliability and clinical utility of remote health applications.Methods:Two novel deep learning(DL)models,YoloTR and YoloMBTR,were developed to detect key ocular surface indicators(OSIs),including tear meniscus height(TMH),non-invasive Keratograph break-up time(NIKBUT),ocular redness,lipid layer,and trichiasis.Additionally,back propagation neural networks(BPNN)and universal network for image segmentation(U-Net)were employed for image classification and segmentation of meibomian gland images to predict Demodex mite infections.These models were trained on a large dataset from high-resolution devices,including Keratograph 5M and various mobile platforms(Huawei,Apple,and Xiaomi).Results:The proposed DL models of YoloMBTR and YoloTR outperformed baseline you only look once(YOLO)models(Yolov5n,Yolov6n,and Yolov8n)across multiple performance metrics,including test average precision(AP),validation AP,and overall accuracy.These two models also exhibit superior performance compared to machine plug-in models in KG5M when benchmarked against the gold standard.Using Python's Matplotlib for visualization and SPSS for statistical analysis,this study introduces an innovative proof-of-concept framework leveraging quantitative AI analysis to address critical challenges in ophthalmology.By integrating advanced DL models,the framework offers a robust approach for detecting and quantifying OSIs with a high degree of precision.This methodological advancement bridges the gap between AI-driven diagnostics and clinical ophthalmology by translating complex ocular data into actionable insights.Conclusions:Integrating AI with clinical laboratory data holds significant potential for advancing mobile eye health(MeHealth),particularly in detecting OSIs.This study aims to explore this integration,focusing on improving diagnostic accuracy and accessibility.This study demonstrates the potential of AI-driven tools in ophthalmic diagnostics,paving the way for reliable,evidence-based solutions in remote patient monitoring and continuous care.The results contribute to the foundation of AI-powered health systems that can extend beyond ophthalmology,improving healthcare accessibility and patient outcomes across various domains.
文摘A convective assembly technique at the micron scale analogous to the writing action of a ＂pipette pen＂ has been developed for the linear assembly of gold nanoparticle strips with micron scale width and millimeter scale length for surface enhanced Raman scattering （SERS）. The arrays with interparticle gaps smaller than 3 nm are hexagonally stacked in the vicinity of the pipette tip. Variable numbers of stacked layers and clean surfaces of the assembled nanoparticles are obtained by optimizing the velocity of the pipette tip. The SERS properties of tile assembled nanoparticle arrays rely on their stacking number and surface cleanliness.
基金supported by the National Natural Science Foundation of China(61376011 and 51402141)Gansu Provincial Natural Science Foundation(17JR5RA198)+1 种基金the Fundamental Research Funds for the Central Universities(lzujbky-2018-119 and lzujbky-2018-ct08)Shenzhen Science and Technology Innovation Committee(JCYJ20170818155813437)。
文摘Nowadays,it is a matter of great concern to design electrode materials with excellent electrochemical performance for supercapacitors by a safe,efficient and simple method.And these characteristics are usually related to the vacancies and impurities in the electrode.To investigate the effect of the vacancies on the electrochemical properties of the supercapacitor cathode material,the uniform reduced CoNi2S4(r-CoNi2S4)nanosheets with sulfur vacancies have been successfully prepared by a one-step hydrothermal method.And the formation of sulfur vacancies are characterized by Raman,X-ray photoelectron spectroscopy and other means.As the electrode for supercapacitor,the r-CoNi2S4 nanosheet electrode delivers a high capacity of 1918.9 Fg-1 at a current density of 1 A g-1,superior rate capability(87.9%retention at a current density of 20 A g-1)and extraordinary cycling stability.Compared with the original CoNi2S4 nanosheet electrode(1226 F g-1at current density of 1 A g-1),the r-CoNi2S4 nanosheet electrode shows a great improvement.The asymmetric supercapacitor based on the r-CoNi2S4 positive electrode and activated carbon negative electrode exhibits a high energy density of 30.3 Wh kg-1 at a power density of 802.1 W kg-1,as well as excellent long-term cycling stability.The feasibility and great potential of the device in practical applications have been successfully proved by lightening the light emitting diodes of three different colors.
基金supported by the Royal Society Research Grant(RGSR1221252).
文摘It is crucial to discover lead-free materials with ultrahigh recoverable energy density(Wrec)that can be employed in future pulse power capacitors.In this work,a high Wrec of 4.51 J/cm^(3) was successfully obtained in lead-free Nd-doped AgNb_(0.8)Ta_(0.2)O_(3) antiferroelectric ceramics at an applied electric field of 290 kV/cm.It is discovered that Nd doping paired with Nb-site vacancies could stabilize the antiferroelectric phase by lowering the temperatures of the M1-M2 and M2-M3 phase transitions,which leads to higher energy storage efficiency.Furthermore,Nd and Ta co-doping will contribute to the electrical homogeneity and low electrical conductivity,resulting in large breakdown strengths.Aliovalent doping in Ag-site with Nb-site vacancies serves as a novel strategy for the construction of AgNbO_(3)-based ceramics with excellent energy storage performance.
