With the approval of more and more genetically modified(GM)crops in our country,GM safety management has become more important.Transgenic detection is a major approach for transgenic safety management.Nevertheless,a c...With the approval of more and more genetically modified(GM)crops in our country,GM safety management has become more important.Transgenic detection is a major approach for transgenic safety management.Nevertheless,a convenient and visual technique with low equipment requirements and high sensitivity for the field detection of GM plants is still lacking.On the basis of the existing recombinase polymerase amplification(RPA)technique,we developed a multiplex RPA(multi-RPA)method that can simultaneously detect three transgenic elements,including the cauliflower mosaic virus 35S gene(CaMV35S)promoter,neomycin phosphotransferaseⅡgene(NptⅡ)and hygromycin B phosphotransferase gene(Hyg),thus improving the detection rate.Moreover,we coupled this multi-RPA technique with the CRISPR/Cas12a reporter system,which enabled the detection results to be clearly observed by naked eyes under ultraviolet(UV)light(254 nm;which could be achieved by a portable UV flashlight),therefore establishing a multi-RPA visual detection technique.Compared with the traditional test strip detection method,this multi-RPA-CRISPR/Cas12a technique has the higher specificity,higher sensitivity,wider application range and lower cost.Compared with other polymerase chain reaction(PCR)techniques,it also has the advantages of low equipment requirements and visualization,making it a potentially feasible method for the field detection of GM plants.展开更多
The polarization properties of light are widely applied in imaging,communications,materials analy⁃sis,and life sciences.Various methods have been developed that can measure the polarization information of a target.How...The polarization properties of light are widely applied in imaging,communications,materials analy⁃sis,and life sciences.Various methods have been developed that can measure the polarization information of a target.However,conventional polarization detection systems are often bulky and complex,limiting their poten⁃tial for broader applications.To address the challenges of miniaturization,integrated polarization detectors have been extensively explored in recent years,achieving significant advancements in performance and functionality.In this review,we focus mainly on integrated polarization detectors with innovative features,including infinitely high polarization discrimination,ultrahigh sensitivity to polarization state change,full Stokes parameters measure⁃ment,and simultaneous perception of polarization and other key properties of light.Lastly,we discuss the oppor⁃tunities and challenges for the future development of integrated polarization photodetectors.展开更多
Bovine serum albumin(BSA)and glycine(Gly)dual-ligand-modified copper nanoclusters(BSA-Gly CuNCs)with high fluorescence intensity were synthesized by a one-pot strategy.Based on the competitive fluorescence quenching a...Bovine serum albumin(BSA)and glycine(Gly)dual-ligand-modified copper nanoclusters(BSA-Gly CuNCs)with high fluorescence intensity were synthesized by a one-pot strategy.Based on the competitive fluorescence quenching and dynamic quenching effects of ornidazole(ONZ)on BSA-Gly CuNCs,a simple and sensitive detection method for ONZ was successfully developed.The experimental results demonstrate that the addition of the small molecule Gly can more effectively protect CuNCs,and thus enhance its fluorescence intensity and stability.The proposed assay allowed for the detection of ONZ in a linear range of 0.28 to 52.60μmol·L^(-1)and a detection limit of 0.069μmol·L^(-1).Compared with the single-ligand-modified CuNCs,dual-ligand-modified BSA-Gly CuNCs had higher fluorescence intensity,stability,and sensing ability and were successfully applied to evaluate ONZ in actual ONZ tablets.展开更多
Herein,copper nanoclusters(Cu NCs)were synthesized in aqueous solution through a chemical reduction method using polyethyleneimine as reducing agent and protective ligand,with Cu(NO_(3))_(2)as copper source.Subse-quen...Herein,copper nanoclusters(Cu NCs)were synthesized in aqueous solution through a chemical reduction method using polyethyleneimine as reducing agent and protective ligand,with Cu(NO_(3))_(2)as copper source.Subse-quently,composite fluorescent nanoparticles,chitosan-functionalized silica nanoparticles(CSNPs)-coated Cu NCs(Cu NCs/CSNPs),were synthesized via a reverse microemulsion method.Compared with Cu NCs,the composite Cu NCs/CSNPs exhibited an increased quantum yield and enhanced fluorescence sensing performance.Based on the composite Cu NCs/CSNPs,a fluorescence method for the detection of cefixime fluorescence quenching was estab-lished.The technique was simple,sensitive,and selective for detecting cefixime.The fluorescence quenching effi-ciency of Cu NCs/CSNPs was linearly related to the concentration of cefixime in the range of 3.98-38.5µmol·L^(-1)(1.81-17.46 mg·L^(-1)),with a limit of detection of 0.0455µmol·L^(-1)(20.6µg·L^(-1)).展开更多
Lunar impact crater detection is crucial for lunar surface studies and spacecraft landing missions,yet deep learning still struggles with accurately detecting small craters,especially when relying on incomplete catalo...Lunar impact crater detection is crucial for lunar surface studies and spacecraft landing missions,yet deep learning still struggles with accurately detecting small craters,especially when relying on incomplete catalogs.In this work,we integrate Digital Elevation Model(DEM)data to construct a high-quality dataset enriched with slope information,enabling a detailed analysis of crater features and effectively improving detection performance in complex terrains and low-contrast areas.Based on this foundation,we propose a novel two-stage detection network,MSFNet,which leverages multi-scale adaptive feature fusion and multisize ROI pooling to enhance the recognition of craters across various scales.Experimental results demonstrate that MSFNet achieves an F1 score of 74.8%on Test Region1 and a recall rate of 87%for craters with diameters larger than 2 km.Moreover,it shows exceptional performance in detecting sub-kilometer craters by successfully identifying a large number of high-confidence,previously unlabeled targets with a low false detection rate confirmed through manual review.This approach offers an efficient and reliable deep learning solution for lunar impact crater detection.展开更多
Human disturbance activities is one of the main reasons for inducing geohazards.Ecological impact assessment metrics of roads are inconsistent criteria and multiple.From the perspective of visual observation,the envir...Human disturbance activities is one of the main reasons for inducing geohazards.Ecological impact assessment metrics of roads are inconsistent criteria and multiple.From the perspective of visual observation,the environment damage can be shown through detecting the uncovered area of vegetation in the images along road.To realize this,an end-to-end environment damage detection model based on convolutional neural network is proposed.A 50-layer residual network is used to extract feature map.The initial parameters are optimized by transfer learning.An example is shown by this method.The dataset including cliff and landslide damage are collected by us along road in Shennongjia national forest park.Results show 0.4703 average precision(AP)rating for cliff damage and 0.4809 average precision(AP)rating for landslide damage.Compared with YOLOv3,our model shows a better accuracy in cliff and landslide detection although a certain amount of speed is sacrificed.展开更多
The rapid integration of Internet of Things(IoT)technologies is reshaping the global energy landscape by deploying smart meters that enable high-resolution consumption monitoring,two-way communication,and advanced met...The rapid integration of Internet of Things(IoT)technologies is reshaping the global energy landscape by deploying smart meters that enable high-resolution consumption monitoring,two-way communication,and advanced metering infrastructure services.However,this digital transformation also exposes power system to evolving threats,ranging from cyber intrusions and electricity theft to device malfunctions,and the unpredictable nature of these anomalies,coupled with the scarcity of labeled fault data,makes realtime detection exceptionally challenging.To address these difficulties,a real-time decision support framework is presented for smart meter anomality detection that leverages rolling time windows and two self-supervised contrastive learning modules.The first module synthesizes diverse negative samples to overcome the lack of labeled anomalies,while the second captures intrinsic temporal patterns for enhanced contextual discrimination.The end-to-end framework continuously updates its model with rolling updated meter data to deliver timely identification of emerging abnormal behaviors in evolving grids.Extensive evaluations on eight publicly available smart meter datasets over seven diverse abnormal patterns testing demonstrate the effectiveness of the proposed full framework,achieving average recall and F1 score of more than 0.85.展开更多
Two new complexes,[Zn_(2)(L1)(HL1)(NO_(3))]·CH_(3)OH(1)and[Zn_(3)(L2)(L3)_(3)Cl]·CH_(3)OH(2),were successfully synthesized by‘one-pot’method based on cinnoline-3-ylhydrazine ligand and zinc with 2-hydroxy-...Two new complexes,[Zn_(2)(L1)(HL1)(NO_(3))]·CH_(3)OH(1)and[Zn_(3)(L2)(L3)_(3)Cl]·CH_(3)OH(2),were successfully synthesized by‘one-pot’method based on cinnoline-3-ylhydrazine ligand and zinc with 2-hydroxy-4-methoxybenzaldehyde and 2-hydroxy-3-methoxybenzaldehyde ligands,respectively,where H_(2)L1=5-methoxy-2-(phthalazin-1-ylhydrazonomethyl)-phenol,H_(2)L2=2-methoxy-6-(phthalazin-1-yl-hydrazonomethyl)-phenol,HL3=2-(1,8-dihydro-[1,2,4]triazolo[3,4-α]phthalazin-3-yl)-6-methoxy-phenol.Complexes 1 and 2 were characterized by infrared spectroscopy,elemental analysis,single-crystal X-ray diffraction,powder X-ray diffraction,etc.It is worth noting that the cinnolin-3-yl-hydrazine ligand and 2-hydroxy-3-methoxybenzaldehyde form two types of Schiff bases(H_(2)L2 and HL3)when in situ reacting and coordinating with Zn(Ⅱ),and HL3 also has two coordination modes.In addition,the fluorescence performance showed that complex 1 can achieve selective and sensitive sensing of Al^(3+)in water with a detection limit of 6.37μmol·L^(-1).CCDC:2413978,1;2413979,2.展开更多
In recent years,with the development of synthetic aperture radar(SAR)technology and the widespread application of deep learning,lightweight detection of SAR images has emerged as a research direction.The ultimate goal...In recent years,with the development of synthetic aperture radar(SAR)technology and the widespread application of deep learning,lightweight detection of SAR images has emerged as a research direction.The ultimate goal is to reduce computational and storage requirements while ensuring detection accuracy and reliability,making it an ideal choice for achieving rapid response and efficient processing.In this regard,a lightweight SAR ship target detection algorithm based on YOLOv8 was proposed in this study.Firstly,the C2f-Sc module was designed by fusing the C2f in the backbone network with the ScConv to reduce spatial redundancy and channel redundancy between features in convolutional neural networks.At the same time,the Ghost module was introduced into the neck network to effectively reduce model parameters and computational complexity.A relatively lightweight EMA attention mechanism was added to the neck network to promote the effective fusion of features at different levels.Experimental results showed that the Parameters and GFLOPs of the improved model are reduced by 8.5%and 7.0%when mAP@0.5 and mAP@0.5:0.95 are increased by 0.7%and 1.8%,respectively.It makes the model lightweight and improves the detection accuracy,which has certain application value.展开更多
Detection of target analytes at low concentrations is significant in various fields,including pharmaceuticals,healthcare,and environmental protection.Theophylline(TP),a natural alkaloid used as a bronchodilator to tre...Detection of target analytes at low concentrations is significant in various fields,including pharmaceuticals,healthcare,and environmental protection.Theophylline(TP),a natural alkaloid used as a bronchodilator to treat respiratory disorders such as asthma,bronchitis,and emphysema,has a narrow therapeutic window with a safe plasma concentration ranging from 55.5-111.0μmol·L^(-1)in adults.Accurate monitoring of TP levels is essential because too low or too high can cause se-rious side effects.In this regard,non-enzymatic electrochemical sensors offer a practical solution with rapidity,portability,and high sensitivity.This article aims to provide a comprehensive review of the recent developments of non-enzymatic electrochemical sensors for TP detection,highlighting the basic principles,electro-oxidation mechanisms,catalytic effects,and the role of modifying materials on electrode performance.Carbon-based electrodes such as glassy carbon electrodes(GCEs),carbon paste electrodes(CPEs),and carbon screen-printed electrodes(SPCEs)have become the primary choices for non-enzymatic sensors due to their chemical stability,low cost,and flexibility in modification.This article identifies the sig-nificant contribution of various modifying materials,including nanomaterials such as carbon nanotubes(CNTs),graphene,metal oxides,and multi-element nanocomposites.These modifications enhance sensors’electron transfer,sensitivity,and selectivity in detecting TP at low concentrations in complex media such as blood plasma and pharmaceutical samples.The electro-oxidation mechanism of TP is also discussed in depth,emphasizing the hydroxyl and carbonyl reaction pathways strongly influenced by pH and electrode materials.These mechanisms guide the selection of the appropriate electrode ma-terial for a particular application.The main contribution of this article is to identify superior modifying materials that can improve the performance of non-enzymatic electrochemical sensors.In a recent study,the combination of multi-element nanocomposites based on titanium dioxide(TiO_(2)),CNTs,and gold nanoparticles(AuNPs)resulted in the lowest detection limit of 3×10^(-5)μmol·L^(-1),reflecting the great potential of these materials for developing high-performance electrochemical sensors.The main conclusion of this article is the importance of a multidisciplinary approach in electrode material design to support the sensitivity and selectivity of TP detection.In addition,there is still a research gap in understanding TP’s more detailed oxidation mechanism,especially under pH variations and complex environments.Therefore,further research on electrode modification and analysis of the TP oxidation mechanism are urgently needed to improve the accuracy and sta-bility of the sensor while expanding its applications in pharmaceutical monitoring and medical diagnostics.By integrating various innovative materials and technical approaches,this review is expected to be an essential reference for developing efficient and affordable non-enzymatic electrochemical sensors.展开更多
The abnormal metabolic activity of the tumor can increase the oxygen consumption in tumor cells,and the poor blood perfusion often happens in tumor regions as well,which are the main reasons that result in a hypoxic s...The abnormal metabolic activity of the tumor can increase the oxygen consumption in tumor cells,and the poor blood perfusion often happens in tumor regions as well,which are the main reasons that result in a hypoxic situation in the tumor.A fluorescence probe,AQD,with selective response toward hypoxia was designed for the detection of hypoxic tumor cells,which was obtained by the covalent connection of a large planar conjugated fluorophore with good fluorescence stability and a N,N-dimethylaniline moiety via the azo bond.The introduction of the azo bond in AQD caused significant fluorescence emission quenching,and the probe was reduced under hypoxic conditions to release the fluorophore via breaking the azo bond,resulting in the gradual recovery of fluorescence emission.Probe AQD exhibited a remarkable fluorescence response in hypoxic conditions,high selectivity,and good biocompatibility,which was successfully used for the imaging of hypoxic tumor cells and realized the detection of hypoxic A549 cells.展开更多
This paper presents a high-speed and robust dual-band infrared thermal camera based on an ARM CPU.The system consists of a low-resolution long-wavelength infrared detector,a digital temperature and humid⁃ity sensor,an...This paper presents a high-speed and robust dual-band infrared thermal camera based on an ARM CPU.The system consists of a low-resolution long-wavelength infrared detector,a digital temperature and humid⁃ity sensor,and a CMOS sensor.In view of the significant contrast between face and background in thermal infra⁃red images,this paper explores a suitable accuracy-latency tradeoff for thermal face detection and proposes a tiny,lightweight detector named YOLO-Fastest-IR.Four YOLO-Fastest-IR models(IR0 to IR3)with different scales are designed based on YOLO-Fastest.To train and evaluate these lightweight models,a multi-user low-resolution thermal face database(RGBT-MLTF)was collected,and the four networks were trained.Experiments demon⁃strate that the lightweight convolutional neural network performs well in thermal infrared face detection tasks.The proposed algorithm outperforms existing face detection methods in both positioning accuracy and speed,making it more suitable for deployment on mobile platforms or embedded devices.After obtaining the region of interest(ROI)in the infrared(IR)image,the RGB camera is guided by the thermal infrared face detection results to achieve fine positioning of the RGB face.Experimental results show that YOLO-Fastest-IR achieves a frame rate of 92.9 FPS on a Raspberry Pi 4B and successfully detects 97.4%of faces in the RGBT-MLTF test set.Ultimate⁃ly,an infrared temperature measurement system with low cost,strong robustness,and high real-time perfor⁃mance was integrated,achieving a temperature measurement accuracy of 0.3℃.展开更多
For segmented detectors,surface flatness is critical as it directly influences both energy resolution and image clarity.Additionally,the limited adjustment range of the segmented detectors necessitates precise benchma...For segmented detectors,surface flatness is critical as it directly influences both energy resolution and image clarity.Additionally,the limited adjustment range of the segmented detectors necessitates precise benchmark construction.This paper proposes an architecture for detecting detector flatness based on channel spectral dispersion.By measuring the dispersion fringes for coplanar adjustment,the final adjustment residual is improved to better than 300 nm.This result validates the feasibility of the proposed technology and provides significant technical support for the development of next-generation large-aperture sky survey equipment.展开更多
We used the natural product chamomile as a carbon source to synthesize praseodymium(Pr) and nitrogen(N) co-doped biomass carbon dots(Pr/N-BCDs) with remarkable luminescence properties by one-step hydrothermal method.C...We used the natural product chamomile as a carbon source to synthesize praseodymium(Pr) and nitrogen(N) co-doped biomass carbon dots(Pr/N-BCDs) with remarkable luminescence properties by one-step hydrothermal method.Compared with single N-doped BCDs(N-BCDs) and Pr-doped BCDs(Pr-BCDs),Pr/N-BCDs not only showed better fluorescence properties and stability but also achieved a significant increase in quantum yield of 12%.More importantly,under certain conditions,Pr/N-BCDs and 2,4-dinitrophenylhydrazide(2,4-DNPH) had significant fluorescence internal filtration effect(IFE) and dynamic quenching effect,and in the concentration range of0.50-20 μmol·L^(-1),the concentration of 2,4-DNPH had a good linear relationship with the fluorescence quenching signal,and the detection limit was as low as 2.1 nmol·L^(-1).展开更多
An in-pixel histogramming time-to-digital converter(hTDC)based on octonary search and 4-tap phase detection is presented,aiming to improve frame rate while ensuring high precicion.The proposed hTDC is a 12-bit two-ste...An in-pixel histogramming time-to-digital converter(hTDC)based on octonary search and 4-tap phase detection is presented,aiming to improve frame rate while ensuring high precicion.The proposed hTDC is a 12-bit two-step converter consisting of a 6-bit coarse quantization and a 6-bit fine quantization,which supports a time resolution of 120 ps and multiphoton counting up to 2 GHz without a GHz reference frequency.The proposed hTDC is designed in 0.11μm CMOS process with an area consumption of 6900μm^(2).The data from a behavioral-level model is imported into the designed hTDC circuit for simulation verification.The post-simulation results show that the proposed hTDC achieves 0.8%depth precision in 9 m range for short-range system design specifications and 0.2%depth precision in 48 m range for long-range system design specifications.Under 30×10^(3) lux background light conditions,the proposed hTDC can be used for SPAD-based flash LiDAR sensor to achieve a frame rate to 40 fps with 200 ps resolution in 9 m range.展开更多
基金the Experimental Technology Research Project of Zhejiang University(SYB202138)National Natural Science Foundation of China(32000195)。
文摘With the approval of more and more genetically modified(GM)crops in our country,GM safety management has become more important.Transgenic detection is a major approach for transgenic safety management.Nevertheless,a convenient and visual technique with low equipment requirements and high sensitivity for the field detection of GM plants is still lacking.On the basis of the existing recombinase polymerase amplification(RPA)technique,we developed a multiplex RPA(multi-RPA)method that can simultaneously detect three transgenic elements,including the cauliflower mosaic virus 35S gene(CaMV35S)promoter,neomycin phosphotransferaseⅡgene(NptⅡ)and hygromycin B phosphotransferase gene(Hyg),thus improving the detection rate.Moreover,we coupled this multi-RPA technique with the CRISPR/Cas12a reporter system,which enabled the detection results to be clearly observed by naked eyes under ultraviolet(UV)light(254 nm;which could be achieved by a portable UV flashlight),therefore establishing a multi-RPA visual detection technique.Compared with the traditional test strip detection method,this multi-RPA-CRISPR/Cas12a technique has the higher specificity,higher sensitivity,wider application range and lower cost.Compared with other polymerase chain reaction(PCR)techniques,it also has the advantages of low equipment requirements and visualization,making it a potentially feasible method for the field detection of GM plants.
基金Supported by the National Key Research and Development Program of China(2022YFA1404602)the Strategic Priority Research Program of the Chinese Academy of Sciences(XDB0580000)+3 种基金the National Natural Science Foundation of China(U23B2045,62305362)the Program of Shanghai Academic/Technology Research Leader(22XD1424400)the Fund of SITP Innovation Foundation(CX-461 and CX-522)Special Project to Seize the Commanding Heights of Science and Technology of Chinese Academy of Sciences,subtopic(GJ0090406-6).
文摘The polarization properties of light are widely applied in imaging,communications,materials analy⁃sis,and life sciences.Various methods have been developed that can measure the polarization information of a target.However,conventional polarization detection systems are often bulky and complex,limiting their poten⁃tial for broader applications.To address the challenges of miniaturization,integrated polarization detectors have been extensively explored in recent years,achieving significant advancements in performance and functionality.In this review,we focus mainly on integrated polarization detectors with innovative features,including infinitely high polarization discrimination,ultrahigh sensitivity to polarization state change,full Stokes parameters measure⁃ment,and simultaneous perception of polarization and other key properties of light.Lastly,we discuss the oppor⁃tunities and challenges for the future development of integrated polarization photodetectors.
文摘Bovine serum albumin(BSA)and glycine(Gly)dual-ligand-modified copper nanoclusters(BSA-Gly CuNCs)with high fluorescence intensity were synthesized by a one-pot strategy.Based on the competitive fluorescence quenching and dynamic quenching effects of ornidazole(ONZ)on BSA-Gly CuNCs,a simple and sensitive detection method for ONZ was successfully developed.The experimental results demonstrate that the addition of the small molecule Gly can more effectively protect CuNCs,and thus enhance its fluorescence intensity and stability.The proposed assay allowed for the detection of ONZ in a linear range of 0.28 to 52.60μmol·L^(-1)and a detection limit of 0.069μmol·L^(-1).Compared with the single-ligand-modified CuNCs,dual-ligand-modified BSA-Gly CuNCs had higher fluorescence intensity,stability,and sensing ability and were successfully applied to evaluate ONZ in actual ONZ tablets.
文摘Herein,copper nanoclusters(Cu NCs)were synthesized in aqueous solution through a chemical reduction method using polyethyleneimine as reducing agent and protective ligand,with Cu(NO_(3))_(2)as copper source.Subse-quently,composite fluorescent nanoparticles,chitosan-functionalized silica nanoparticles(CSNPs)-coated Cu NCs(Cu NCs/CSNPs),were synthesized via a reverse microemulsion method.Compared with Cu NCs,the composite Cu NCs/CSNPs exhibited an increased quantum yield and enhanced fluorescence sensing performance.Based on the composite Cu NCs/CSNPs,a fluorescence method for the detection of cefixime fluorescence quenching was estab-lished.The technique was simple,sensitive,and selective for detecting cefixime.The fluorescence quenching effi-ciency of Cu NCs/CSNPs was linearly related to the concentration of cefixime in the range of 3.98-38.5µmol·L^(-1)(1.81-17.46 mg·L^(-1)),with a limit of detection of 0.0455µmol·L^(-1)(20.6µg·L^(-1)).
基金National Natural Science Foundation of China(12103020,12363009)Natural Science Foundation of Jiangxi Province(20224BAB211011)+1 种基金Open Project Program of State Key Laboratory of Lunar and Planetary Sciences(Macao University of Science and Technology)(Macao FDCT grant No.002/2024/SKL)Youth Talent Project of Science and Technology Plan of Ganzhou(2022CXRC9191,2023CYZ26970)。
文摘Lunar impact crater detection is crucial for lunar surface studies and spacecraft landing missions,yet deep learning still struggles with accurately detecting small craters,especially when relying on incomplete catalogs.In this work,we integrate Digital Elevation Model(DEM)data to construct a high-quality dataset enriched with slope information,enabling a detailed analysis of crater features and effectively improving detection performance in complex terrains and low-contrast areas.Based on this foundation,we propose a novel two-stage detection network,MSFNet,which leverages multi-scale adaptive feature fusion and multisize ROI pooling to enhance the recognition of craters across various scales.Experimental results demonstrate that MSFNet achieves an F1 score of 74.8%on Test Region1 and a recall rate of 87%for craters with diameters larger than 2 km.Moreover,it shows exceptional performance in detecting sub-kilometer craters by successfully identifying a large number of high-confidence,previously unlabeled targets with a low false detection rate confirmed through manual review.This approach offers an efficient and reliable deep learning solution for lunar impact crater detection.
文摘Human disturbance activities is one of the main reasons for inducing geohazards.Ecological impact assessment metrics of roads are inconsistent criteria and multiple.From the perspective of visual observation,the environment damage can be shown through detecting the uncovered area of vegetation in the images along road.To realize this,an end-to-end environment damage detection model based on convolutional neural network is proposed.A 50-layer residual network is used to extract feature map.The initial parameters are optimized by transfer learning.An example is shown by this method.The dataset including cliff and landslide damage are collected by us along road in Shennongjia national forest park.Results show 0.4703 average precision(AP)rating for cliff damage and 0.4809 average precision(AP)rating for landslide damage.Compared with YOLOv3,our model shows a better accuracy in cliff and landslide detection although a certain amount of speed is sacrificed.
文摘The rapid integration of Internet of Things(IoT)technologies is reshaping the global energy landscape by deploying smart meters that enable high-resolution consumption monitoring,two-way communication,and advanced metering infrastructure services.However,this digital transformation also exposes power system to evolving threats,ranging from cyber intrusions and electricity theft to device malfunctions,and the unpredictable nature of these anomalies,coupled with the scarcity of labeled fault data,makes realtime detection exceptionally challenging.To address these difficulties,a real-time decision support framework is presented for smart meter anomality detection that leverages rolling time windows and two self-supervised contrastive learning modules.The first module synthesizes diverse negative samples to overcome the lack of labeled anomalies,while the second captures intrinsic temporal patterns for enhanced contextual discrimination.The end-to-end framework continuously updates its model with rolling updated meter data to deliver timely identification of emerging abnormal behaviors in evolving grids.Extensive evaluations on eight publicly available smart meter datasets over seven diverse abnormal patterns testing demonstrate the effectiveness of the proposed full framework,achieving average recall and F1 score of more than 0.85.
文摘Two new complexes,[Zn_(2)(L1)(HL1)(NO_(3))]·CH_(3)OH(1)and[Zn_(3)(L2)(L3)_(3)Cl]·CH_(3)OH(2),were successfully synthesized by‘one-pot’method based on cinnoline-3-ylhydrazine ligand and zinc with 2-hydroxy-4-methoxybenzaldehyde and 2-hydroxy-3-methoxybenzaldehyde ligands,respectively,where H_(2)L1=5-methoxy-2-(phthalazin-1-ylhydrazonomethyl)-phenol,H_(2)L2=2-methoxy-6-(phthalazin-1-yl-hydrazonomethyl)-phenol,HL3=2-(1,8-dihydro-[1,2,4]triazolo[3,4-α]phthalazin-3-yl)-6-methoxy-phenol.Complexes 1 and 2 were characterized by infrared spectroscopy,elemental analysis,single-crystal X-ray diffraction,powder X-ray diffraction,etc.It is worth noting that the cinnolin-3-yl-hydrazine ligand and 2-hydroxy-3-methoxybenzaldehyde form two types of Schiff bases(H_(2)L2 and HL3)when in situ reacting and coordinating with Zn(Ⅱ),and HL3 also has two coordination modes.In addition,the fluorescence performance showed that complex 1 can achieve selective and sensitive sensing of Al^(3+)in water with a detection limit of 6.37μmol·L^(-1).CCDC:2413978,1;2413979,2.
文摘In recent years,with the development of synthetic aperture radar(SAR)technology and the widespread application of deep learning,lightweight detection of SAR images has emerged as a research direction.The ultimate goal is to reduce computational and storage requirements while ensuring detection accuracy and reliability,making it an ideal choice for achieving rapid response and efficient processing.In this regard,a lightweight SAR ship target detection algorithm based on YOLOv8 was proposed in this study.Firstly,the C2f-Sc module was designed by fusing the C2f in the backbone network with the ScConv to reduce spatial redundancy and channel redundancy between features in convolutional neural networks.At the same time,the Ghost module was introduced into the neck network to effectively reduce model parameters and computational complexity.A relatively lightweight EMA attention mechanism was added to the neck network to promote the effective fusion of features at different levels.Experimental results showed that the Parameters and GFLOPs of the improved model are reduced by 8.5%and 7.0%when mAP@0.5 and mAP@0.5:0.95 are increased by 0.7%and 1.8%,respectively.It makes the model lightweight and improves the detection accuracy,which has certain application value.
基金the funding from Lembaga Penelitian dan Pengabdian Masyarakat(LPPM)Universitas Indonesia,by Riset Kolaborasi Indonesia(RKI)-World Class University(WCU)Program with grant number NKB-1067/UN2-RST/HKP.05.00/2023 and NKB-781/UN2.RST/HKP.05.00/2024.
文摘Detection of target analytes at low concentrations is significant in various fields,including pharmaceuticals,healthcare,and environmental protection.Theophylline(TP),a natural alkaloid used as a bronchodilator to treat respiratory disorders such as asthma,bronchitis,and emphysema,has a narrow therapeutic window with a safe plasma concentration ranging from 55.5-111.0μmol·L^(-1)in adults.Accurate monitoring of TP levels is essential because too low or too high can cause se-rious side effects.In this regard,non-enzymatic electrochemical sensors offer a practical solution with rapidity,portability,and high sensitivity.This article aims to provide a comprehensive review of the recent developments of non-enzymatic electrochemical sensors for TP detection,highlighting the basic principles,electro-oxidation mechanisms,catalytic effects,and the role of modifying materials on electrode performance.Carbon-based electrodes such as glassy carbon electrodes(GCEs),carbon paste electrodes(CPEs),and carbon screen-printed electrodes(SPCEs)have become the primary choices for non-enzymatic sensors due to their chemical stability,low cost,and flexibility in modification.This article identifies the sig-nificant contribution of various modifying materials,including nanomaterials such as carbon nanotubes(CNTs),graphene,metal oxides,and multi-element nanocomposites.These modifications enhance sensors’electron transfer,sensitivity,and selectivity in detecting TP at low concentrations in complex media such as blood plasma and pharmaceutical samples.The electro-oxidation mechanism of TP is also discussed in depth,emphasizing the hydroxyl and carbonyl reaction pathways strongly influenced by pH and electrode materials.These mechanisms guide the selection of the appropriate electrode ma-terial for a particular application.The main contribution of this article is to identify superior modifying materials that can improve the performance of non-enzymatic electrochemical sensors.In a recent study,the combination of multi-element nanocomposites based on titanium dioxide(TiO_(2)),CNTs,and gold nanoparticles(AuNPs)resulted in the lowest detection limit of 3×10^(-5)μmol·L^(-1),reflecting the great potential of these materials for developing high-performance electrochemical sensors.The main conclusion of this article is the importance of a multidisciplinary approach in electrode material design to support the sensitivity and selectivity of TP detection.In addition,there is still a research gap in understanding TP’s more detailed oxidation mechanism,especially under pH variations and complex environments.Therefore,further research on electrode modification and analysis of the TP oxidation mechanism are urgently needed to improve the accuracy and sta-bility of the sensor while expanding its applications in pharmaceutical monitoring and medical diagnostics.By integrating various innovative materials and technical approaches,this review is expected to be an essential reference for developing efficient and affordable non-enzymatic electrochemical sensors.
文摘The abnormal metabolic activity of the tumor can increase the oxygen consumption in tumor cells,and the poor blood perfusion often happens in tumor regions as well,which are the main reasons that result in a hypoxic situation in the tumor.A fluorescence probe,AQD,with selective response toward hypoxia was designed for the detection of hypoxic tumor cells,which was obtained by the covalent connection of a large planar conjugated fluorophore with good fluorescence stability and a N,N-dimethylaniline moiety via the azo bond.The introduction of the azo bond in AQD caused significant fluorescence emission quenching,and the probe was reduced under hypoxic conditions to release the fluorophore via breaking the azo bond,resulting in the gradual recovery of fluorescence emission.Probe AQD exhibited a remarkable fluorescence response in hypoxic conditions,high selectivity,and good biocompatibility,which was successfully used for the imaging of hypoxic tumor cells and realized the detection of hypoxic A549 cells.
基金Supported by the Fundamental Research Funds for the Central Universities(2024300443)the Natural Science Foundation of Jiangsu Province(BK20241224).
文摘This paper presents a high-speed and robust dual-band infrared thermal camera based on an ARM CPU.The system consists of a low-resolution long-wavelength infrared detector,a digital temperature and humid⁃ity sensor,and a CMOS sensor.In view of the significant contrast between face and background in thermal infra⁃red images,this paper explores a suitable accuracy-latency tradeoff for thermal face detection and proposes a tiny,lightweight detector named YOLO-Fastest-IR.Four YOLO-Fastest-IR models(IR0 to IR3)with different scales are designed based on YOLO-Fastest.To train and evaluate these lightweight models,a multi-user low-resolution thermal face database(RGBT-MLTF)was collected,and the four networks were trained.Experiments demon⁃strate that the lightweight convolutional neural network performs well in thermal infrared face detection tasks.The proposed algorithm outperforms existing face detection methods in both positioning accuracy and speed,making it more suitable for deployment on mobile platforms or embedded devices.After obtaining the region of interest(ROI)in the infrared(IR)image,the RGB camera is guided by the thermal infrared face detection results to achieve fine positioning of the RGB face.Experimental results show that YOLO-Fastest-IR achieves a frame rate of 92.9 FPS on a Raspberry Pi 4B and successfully detects 97.4%of faces in the RGBT-MLTF test set.Ultimate⁃ly,an infrared temperature measurement system with low cost,strong robustness,and high real-time perfor⁃mance was integrated,achieving a temperature measurement accuracy of 0.3℃.
文摘For segmented detectors,surface flatness is critical as it directly influences both energy resolution and image clarity.Additionally,the limited adjustment range of the segmented detectors necessitates precise benchmark construction.This paper proposes an architecture for detecting detector flatness based on channel spectral dispersion.By measuring the dispersion fringes for coplanar adjustment,the final adjustment residual is improved to better than 300 nm.This result validates the feasibility of the proposed technology and provides significant technical support for the development of next-generation large-aperture sky survey equipment.
基金supported by the National Natural Science Foundation of China (Grant No.22063010)the Natural Science Foundation of Shaanxi Province (Grant No.2022QFY07-05)Yan'an Science and Technology Plan Project (Grants No.2022SLJBZ-002, 2023-CYL-193)。
文摘We used the natural product chamomile as a carbon source to synthesize praseodymium(Pr) and nitrogen(N) co-doped biomass carbon dots(Pr/N-BCDs) with remarkable luminescence properties by one-step hydrothermal method.Compared with single N-doped BCDs(N-BCDs) and Pr-doped BCDs(Pr-BCDs),Pr/N-BCDs not only showed better fluorescence properties and stability but also achieved a significant increase in quantum yield of 12%.More importantly,under certain conditions,Pr/N-BCDs and 2,4-dinitrophenylhydrazide(2,4-DNPH) had significant fluorescence internal filtration effect(IFE) and dynamic quenching effect,and in the concentration range of0.50-20 μmol·L^(-1),the concentration of 2,4-DNPH had a good linear relationship with the fluorescence quenching signal,and the detection limit was as low as 2.1 nmol·L^(-1).
基金National Key Research and Development Program of China(2022YFB2804401)。
文摘An in-pixel histogramming time-to-digital converter(hTDC)based on octonary search and 4-tap phase detection is presented,aiming to improve frame rate while ensuring high precicion.The proposed hTDC is a 12-bit two-step converter consisting of a 6-bit coarse quantization and a 6-bit fine quantization,which supports a time resolution of 120 ps and multiphoton counting up to 2 GHz without a GHz reference frequency.The proposed hTDC is designed in 0.11μm CMOS process with an area consumption of 6900μm^(2).The data from a behavioral-level model is imported into the designed hTDC circuit for simulation verification.The post-simulation results show that the proposed hTDC achieves 0.8%depth precision in 9 m range for short-range system design specifications and 0.2%depth precision in 48 m range for long-range system design specifications.Under 30×10^(3) lux background light conditions,the proposed hTDC can be used for SPAD-based flash LiDAR sensor to achieve a frame rate to 40 fps with 200 ps resolution in 9 m range.
