Cooperative communication can achieve spatial diversity gains,and consequently combats signal fading due to multipath propagation in wireless networks powerfully.A novel complex field network-coded cooperation（CFNCC...Cooperative communication can achieve spatial diversity gains,and consequently combats signal fading due to multipath propagation in wireless networks powerfully.A novel complex field network-coded cooperation（CFNCC） scheme based on multi-user detection for the multiple unicast transmission is proposed.Theoretic analysis and simulation results demonstrate that,compared with the conventional cooperation（CC） scheme and network-coded cooperation（NCC） scheme,CFNCC would obtain higher network throughput and consumes less time slots.Moreover,a further investigation is made for the symbol error probability（SEP） performance of CFNCC scheme,and SEPs of CFNCC scheme are compared with those of NCC scheme in various scenarios for different signal to noise ratio（SNR） values.展开更多
Multi-user detection (MUD) based on multirate transmission in code division multiple access (CDMA) system is discussed. Under the requirement of signal interference ratio (SIR) detection at base station and framework ...Multi-user detection (MUD) based on multirate transmission in code division multiple access (CDMA) system is discussed. Under the requirement of signal interference ratio (SIR) detection at base station and framework with parallel interference cancellation, a supervision decision algorithm based on pre-decision of probabilistic data association (PDA) and hard decision is proposed. The detection performance is analyzed and simulation is implemented to show that the supervision decision algorithm improves the detection performance effectively.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
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
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
A measurement system for the scattering characteristics of warhead fragments based on high-speed imaging systems offers advantages such as simple deployment,flexible maneuverability,and high spatiotemporal resolution,...A measurement system for the scattering characteristics of warhead fragments based on high-speed imaging systems offers advantages such as simple deployment,flexible maneuverability,and high spatiotemporal resolution,enabling the acquisition of full-process data of the fragment scattering process.However,mismatches between camera frame rates and target velocities can lead to long motion blur tails of high-speed fragment targets,resulting in low signal-to-noise ratios and rendering conventional detection algorithms ineffective in dynamic strong interference testing environments.In this study,we propose a detection framework centered on dynamic strong interference disturbance signal separation and suppression.We introduce a mixture Gaussian model constrained under a joint spatialtemporal-transform domain Dirichlet process,combined with total variation regularization to achieve disturbance signal suppression.Experimental results demonstrate that the proposed disturbance suppression method can be integrated with certain conventional motion target detection tasks,enabling adaptation to real-world data to a certain extent.Moreover,we provide a specific implementation of this process,which achieves a detection rate close to 100%with an approximate 0%false alarm rate in multiple sets of real target field test data.This research effectively advances the development of the field of damage parameter testing.展开更多
Calcium ions(Ca^(2+))and manganese ions(Mn^(2+))are essential for sustaining life activities and are key monitoring indicators in drinking water.Developing highly sensitive,selective,and portable detection methods for...Calcium ions(Ca^(2+))and manganese ions(Mn^(2+))are essential for sustaining life activities and are key monitoring indicators in drinking water.Developing highly sensitive,selective,and portable detection methods for Ca^(2+)and Mn^(2+)is significant for water quality monitoring and human health.In this paper,blue fluorescent Ti3C2 MXene-based quantum dots(MQDs,λ_(em)=445 nm)are prepared using Ti_(3)C_(2)MXene as the precursor.Through the chelation effect of ethylene diamine tetraacetic acid(EDTA),a blue and red dual-emission fluorescent probe,MQDs-EDTA-Eu^(3+)-DPA,was constructed.Herein,dipicolinic acid(DPA)acts as an absorbing ligand and significantly enhances the red fluorescence of europium ions(Eu^(3+))at 616 nm through the“antenna effect”.The blue fluorescence of MQDs serves as an internal reference signal.High concentrations of Ca^(2+)can quench the red fluorescence of Eu^(3+)-DPA;Mn^(2+)can be excited to emit purple fluorescence at 380 nm after coordinating with DPA,red fluorescence of Eu^(3+)-DPA serves as the internal reference signal.Based on the above two fluorescence intensity changes,ratiometric fluorescence detection methods for Ca^(2+)and Mn^(2+)are established.The fluorescence intensity ratio(IF_(616)/IF_(445))exhibits a linear relationship with Ca^(2+)in the range of 35-120μmol/L,with a detection limit of 5.98μmol/L.The fluorescence intensity ratio(IF_(380)/IF_(616))shows good linearity with Mn^(2+)in the range of 0-14μmol/L,with a detection limit of 28.6 nmol/L.This method was successfully applied to the quantitative analysis of Ca^(2+)and Mn^(2+)in commercially available mineral water(Nongfu Spring,Ganten,and Evergrande),with recovery rates of 80.6%-117%and relative standard deviations(RSD)of 0.76%-4.6%.Additionally,by preparing MQD-based fluorescent test strips,visual detections of Ca^(2+)and Mn^(2+)are achieved.This work demonstrates the application potential of MQDs in the field of visual fluorescence sensing of ions in water quality.展开更多
Aiming at the problem that infrared small target detection faces low contrast between the background and the target and insufficient noise suppression ability under the complex cloud background,an infrared small targe...Aiming at the problem that infrared small target detection faces low contrast between the background and the target and insufficient noise suppression ability under the complex cloud background,an infrared small target detection method based on the tensor nuclear norm and direction residual weighting was proposed.Based on converting the infrared image into an infrared patch tensor model,from the perspective of the low-rank nature of the background tensor,and taking advantage of the difference in contrast between the background and the target in different directions,we designed a double-neighborhood local contrast based on direction residual weighting method(DNLCDRW)combined with the partial sum of tensor nuclear norm(PSTNN)to achieve effective background suppression and recovery of infrared small targets.Experiments show that the algorithm is effective in suppressing the background and improving the detection ability of the target.展开更多
Soil DNA extraction,such as microbial community analysis and gene drift detection,is an important basis for multiple analyses in different fields.Nevertheless,the soil DNA extraction methods for field detection are st...Soil DNA extraction,such as microbial community analysis and gene drift detection,is an important basis for multiple analyses in different fields.Nevertheless,the soil DNA extraction methods for field detection are still lacking.This study established a rapid soil DNA extraction(RSDE)method that can be used in field detection.In this method,we first utilized the optimized lysate to isolate DNA from soil and then used a filtration membrane and a DNA adsorption membrane to purify the DNA via the column method.Moreover,we used the pressure from the syringe instead of the conventional centrifugal force of the centrifuge to assist the sample filtration,resulting in very low requirements for this method,with an extraction time of less than 20 min.Furthermore,we demonstrated that the RSDE method was applicable for DNA extraction from different types of soils,with the demand for soil samples as low as 0.1 g and that the amount of obtained DNA was,to some extent,greater than that obtained by a commercial kit.Further analysis revealed that this extracted genomic DNA can be used directly for polymerase chain reaction(PCR)analysis,including ordinary PCR,real-time fluorescent quantitative PCR,and recombinase polymerase amplification(RPA)-CRISPR/Cas12a visual assays.In addition,we demonstrated that this method can be used to extract DNA from residual plant roots in addition to soil microbes,which lays a foundation for the comprehensive analysis of soil plants and microorganisms.In summary,the RSDE method proposed in this study may have wide application prospects.展开更多
To address the challenges of low detection accuracy caused by the diverse species,significant size variations,and complex growth environments of wheat pests in natural settings,a PSA-YOLO11n algorithm is proposed to e...To address the challenges of low detection accuracy caused by the diverse species,significant size variations,and complex growth environments of wheat pests in natural settings,a PSA-YOLO11n algorithm is proposed to enhance detection precision.Building upon the YOLO11n framework,the proposed improvements include three key components:1)SimCSPSPPF in Backbone:An improved Spatial Pyramid Pooling-Fast(SPPF)module,SimCSPSPPF,is integrated into the Backbone to reduce the number of channels in the hidden layers,thereby accelerating model training.2)PEC in Neck:The standard convolution layers in the Neck are replaced with Perception Enhancement Convolutions(PEC)to improve multi-scale feature extraction capabilities,enhancing detection speed.3)AWIoU Loss Function:The regression loss function is replaced with Adequate Wise IoU(AWIoU),addressing issues of bounding box distortion caused by the diversity in pest species and size variations,thereby improving the precision of bounding box localization.Experimental evaluations on the IP102 dataset demonstrate that PSA-YOLO11n achieves a mean Average Precision(mAP)of 89.10%,surpassing YOLO11n by 0.8%.Comparisons with other mainstream algorithms,including Faster R-CNN,RetinaNet,YOLOv5s,YOLOv8n,YOLOv10n,and YOLO11n,confirm that PSA-YOLO11n outperforms all baselines in terms of detection performance.These results highlight the algorithm’s capability to significantly improve the detection accuracy of multi-scale wheat pests in natural environments,providing an effective solution for pest management in wheat production.展开更多
4-Nonylphenol(NP)is a kind of estrogen belonging to the endocrine disrupter,widely used in various agricultural and industrial goods.However,extensive use of NP with direct release to environment poses high risks to b...4-Nonylphenol(NP)is a kind of estrogen belonging to the endocrine disrupter,widely used in various agricultural and industrial goods.However,extensive use of NP with direct release to environment poses high risks to both human health and ecosystems.Herein,for the first time,we developed near-infrared(NIR)responsive upconversion luminescence nanosensor for NP detection.The Förster resonance energy transfer based upconversion nanoparticles(UCNPs)-graphene oxide sensor offers highly selective and sensitive detection of NP in linear ranges of 5−200 ng/mL and 200−1000 ng/mL under 980 nm and 808 nm excitation,respectively,with LOD at 4.2 ng/mL.The sensors were successfully tested for NP detection in real liquid milk samples with excellent recovery results.The rare-earth fluoride based upconversion luminescence nanosensor with NIR excitation wavelength,holds promise for sensing food,environmental,and biological samples due to their high sensitivity,specific recognition,low LOD,negligible autofluorescence,along with the deep penetration of NIR excitation sources.展开更多
Missile-borne short-range infrared detection(SIRD)technology is commonly used in military ground target detection.In complex battlefield environments,achieving precise strike on ground target is a challenging task.How...Missile-borne short-range infrared detection(SIRD)technology is commonly used in military ground target detection.In complex battlefield environments,achieving precise strike on ground target is a challenging task.However,real battlefield data is limited,and equivalent experiments are costly.Currently,there is a lack of comprehensive physical modeling and numerical simulation methods for SIRD.To this end,this study proposes a SIRD simulation framework incorporating full-link physical response,which is integrated through the radiative transfer layer,the sensor response layer,and the model-driven layer.In the radiative transfer layer,a coupled dynamic detection model is established to describe the external optical channel response of the SIRD system by combining the infrared radiation model and the geometric measurement model.In the sensor response layer,considering photoelectric conversion and signal processing,the internal signal response model of the SIRD system is established by a hybrid mode of parametric modeling and analog circuit analysis.In the model-driven layer,a cosimulation application based on a three-dimensional virtual environment is proposed to drive the full-link physical model,and a parallel ray tracing method is employed for real-time synchronous simulation.The proposed simulation framework can provide pixel-level signal output and is verified by the measured data.The evaluation results of the root mean square error(RMSE)and the Pearson correlation coefficient(PCC)show that the simulated data and the measured data achieve good consistency,and the evaluation results of the waveform eigenvalues indicate that the simulated signals exhibit low errors compared to the measured signals.The proposed simulation framework has the potential to acquire large sample datasets of SIRD under various complex battlefield environments and can provide an effective data source for SIRD application research.展开更多
Ant colony optimization(ACO)is a random search algorithm based on probability calculation.However,the uninformed search strategy has a slow convergence speed.The Bayesian algorithm uses the historical information of t...Ant colony optimization(ACO)is a random search algorithm based on probability calculation.However,the uninformed search strategy has a slow convergence speed.The Bayesian algorithm uses the historical information of the searched point to determine the next search point during the search process,reducing the uncertainty in the random search process.Due to the ability of the Bayesian algorithm to reduce uncertainty,a Bayesian ACO algorithm is proposed in this paper to increase the convergence speed of the conventional ACO algorithm for image edge detection.In addition,this paper has the following two innovations on the basis of the classical algorithm,one of which is to add random perturbations after completing the pheromone update.The second is the use of adaptive pheromone heuristics.Experimental results illustrate that the proposed Bayesian ACO algorithm has faster convergence and higher precision and recall than the traditional ant colony algorithm,due to the improvement of the pheromone utilization rate.Moreover,Bayesian ACO algorithm outperforms the other comparative methods in edge detection task.展开更多
基金supported by the National Natural Science Foundation of China(6104000561001126+5 种基金61271262)the China Postdoctoral Science Foundation Funded Project(201104916382012T50789)the Natural Science Foundation of Shannxi Province of China(2011JQ8036)the Special Fund for Basic Scientific Research of Central Colleges (CHD2012ZD005)the Research Fund of Zhejiang University of Technology(20100244)
文摘Cooperative communication can achieve spatial diversity gains,and consequently combats signal fading due to multipath propagation in wireless networks powerfully.A novel complex field network-coded cooperation（CFNCC） scheme based on multi-user detection for the multiple unicast transmission is proposed.Theoretic analysis and simulation results demonstrate that,compared with the conventional cooperation（CC） scheme and network-coded cooperation（NCC） scheme,CFNCC would obtain higher network throughput and consumes less time slots.Moreover,a further investigation is made for the symbol error probability（SEP） performance of CFNCC scheme,and SEPs of CFNCC scheme are compared with those of NCC scheme in various scenarios for different signal to noise ratio（SNR） values.
文摘Multi-user detection (MUD) based on multirate transmission in code division multiple access (CDMA) system is discussed. Under the requirement of signal interference ratio (SIR) detection at base station and framework with parallel interference cancellation, a supervision decision algorithm based on pre-decision of probabilistic data association (PDA) and hard decision is proposed. The detection performance is analyzed and simulation is implemented to show that the supervision decision algorithm improves the detection performance effectively.
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.
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.
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).
文摘A measurement system for the scattering characteristics of warhead fragments based on high-speed imaging systems offers advantages such as simple deployment,flexible maneuverability,and high spatiotemporal resolution,enabling the acquisition of full-process data of the fragment scattering process.However,mismatches between camera frame rates and target velocities can lead to long motion blur tails of high-speed fragment targets,resulting in low signal-to-noise ratios and rendering conventional detection algorithms ineffective in dynamic strong interference testing environments.In this study,we propose a detection framework centered on dynamic strong interference disturbance signal separation and suppression.We introduce a mixture Gaussian model constrained under a joint spatialtemporal-transform domain Dirichlet process,combined with total variation regularization to achieve disturbance signal suppression.Experimental results demonstrate that the proposed disturbance suppression method can be integrated with certain conventional motion target detection tasks,enabling adaptation to real-world data to a certain extent.Moreover,we provide a specific implementation of this process,which achieves a detection rate close to 100%with an approximate 0%false alarm rate in multiple sets of real target field test data.This research effectively advances the development of the field of damage parameter testing.
基金The Tertiary Education Scientific Research Project of the Guangzhou Municipal Education Bureau(2024312227)Innovative and Entrepreneurial Projects of Guangzhou University Students(202411078014)+2 种基金Guangzhou University Open Sharing Fund for Instruments and Equipment(2025)National Major Scientific Research Instrument Development Project(22227804)Sub-subject of the National Key Research Project(2023YFB3210100)。
文摘Calcium ions(Ca^(2+))and manganese ions(Mn^(2+))are essential for sustaining life activities and are key monitoring indicators in drinking water.Developing highly sensitive,selective,and portable detection methods for Ca^(2+)and Mn^(2+)is significant for water quality monitoring and human health.In this paper,blue fluorescent Ti3C2 MXene-based quantum dots(MQDs,λ_(em)=445 nm)are prepared using Ti_(3)C_(2)MXene as the precursor.Through the chelation effect of ethylene diamine tetraacetic acid(EDTA),a blue and red dual-emission fluorescent probe,MQDs-EDTA-Eu^(3+)-DPA,was constructed.Herein,dipicolinic acid(DPA)acts as an absorbing ligand and significantly enhances the red fluorescence of europium ions(Eu^(3+))at 616 nm through the“antenna effect”.The blue fluorescence of MQDs serves as an internal reference signal.High concentrations of Ca^(2+)can quench the red fluorescence of Eu^(3+)-DPA;Mn^(2+)can be excited to emit purple fluorescence at 380 nm after coordinating with DPA,red fluorescence of Eu^(3+)-DPA serves as the internal reference signal.Based on the above two fluorescence intensity changes,ratiometric fluorescence detection methods for Ca^(2+)and Mn^(2+)are established.The fluorescence intensity ratio(IF_(616)/IF_(445))exhibits a linear relationship with Ca^(2+)in the range of 35-120μmol/L,with a detection limit of 5.98μmol/L.The fluorescence intensity ratio(IF_(380)/IF_(616))shows good linearity with Mn^(2+)in the range of 0-14μmol/L,with a detection limit of 28.6 nmol/L.This method was successfully applied to the quantitative analysis of Ca^(2+)and Mn^(2+)in commercially available mineral water(Nongfu Spring,Ganten,and Evergrande),with recovery rates of 80.6%-117%and relative standard deviations(RSD)of 0.76%-4.6%.Additionally,by preparing MQD-based fluorescent test strips,visual detections of Ca^(2+)and Mn^(2+)are achieved.This work demonstrates the application potential of MQDs in the field of visual fluorescence sensing of ions in water quality.
基金Supported by the Key Laboratory Fund for Equipment Pre-Research(6142207210202)。
文摘Aiming at the problem that infrared small target detection faces low contrast between the background and the target and insufficient noise suppression ability under the complex cloud background,an infrared small target detection method based on the tensor nuclear norm and direction residual weighting was proposed.Based on converting the infrared image into an infrared patch tensor model,from the perspective of the low-rank nature of the background tensor,and taking advantage of the difference in contrast between the background and the target in different directions,we designed a double-neighborhood local contrast based on direction residual weighting method(DNLCDRW)combined with the partial sum of tensor nuclear norm(PSTNN)to achieve effective background suppression and recovery of infrared small targets.Experiments show that the algorithm is effective in suppressing the background and improving the detection ability of the target.
基金the Experimental Technology Research Project of Zhejiang University(SYB202138)National Natural Science Foundation of China(32000195).
文摘Soil DNA extraction,such as microbial community analysis and gene drift detection,is an important basis for multiple analyses in different fields.Nevertheless,the soil DNA extraction methods for field detection are still lacking.This study established a rapid soil DNA extraction(RSDE)method that can be used in field detection.In this method,we first utilized the optimized lysate to isolate DNA from soil and then used a filtration membrane and a DNA adsorption membrane to purify the DNA via the column method.Moreover,we used the pressure from the syringe instead of the conventional centrifugal force of the centrifuge to assist the sample filtration,resulting in very low requirements for this method,with an extraction time of less than 20 min.Furthermore,we demonstrated that the RSDE method was applicable for DNA extraction from different types of soils,with the demand for soil samples as low as 0.1 g and that the amount of obtained DNA was,to some extent,greater than that obtained by a commercial kit.Further analysis revealed that this extracted genomic DNA can be used directly for polymerase chain reaction(PCR)analysis,including ordinary PCR,real-time fluorescent quantitative PCR,and recombinase polymerase amplification(RPA)-CRISPR/Cas12a visual assays.In addition,we demonstrated that this method can be used to extract DNA from residual plant roots in addition to soil microbes,which lays a foundation for the comprehensive analysis of soil plants and microorganisms.In summary,the RSDE method proposed in this study may have wide application prospects.
文摘To address the challenges of low detection accuracy caused by the diverse species,significant size variations,and complex growth environments of wheat pests in natural settings,a PSA-YOLO11n algorithm is proposed to enhance detection precision.Building upon the YOLO11n framework,the proposed improvements include three key components:1)SimCSPSPPF in Backbone:An improved Spatial Pyramid Pooling-Fast(SPPF)module,SimCSPSPPF,is integrated into the Backbone to reduce the number of channels in the hidden layers,thereby accelerating model training.2)PEC in Neck:The standard convolution layers in the Neck are replaced with Perception Enhancement Convolutions(PEC)to improve multi-scale feature extraction capabilities,enhancing detection speed.3)AWIoU Loss Function:The regression loss function is replaced with Adequate Wise IoU(AWIoU),addressing issues of bounding box distortion caused by the diversity in pest species and size variations,thereby improving the precision of bounding box localization.Experimental evaluations on the IP102 dataset demonstrate that PSA-YOLO11n achieves a mean Average Precision(mAP)of 89.10%,surpassing YOLO11n by 0.8%.Comparisons with other mainstream algorithms,including Faster R-CNN,RetinaNet,YOLOv5s,YOLOv8n,YOLOv10n,and YOLO11n,confirm that PSA-YOLO11n outperforms all baselines in terms of detection performance.These results highlight the algorithm’s capability to significantly improve the detection accuracy of multi-scale wheat pests in natural environments,providing an effective solution for pest management in wheat production.
文摘4-Nonylphenol(NP)is a kind of estrogen belonging to the endocrine disrupter,widely used in various agricultural and industrial goods.However,extensive use of NP with direct release to environment poses high risks to both human health and ecosystems.Herein,for the first time,we developed near-infrared(NIR)responsive upconversion luminescence nanosensor for NP detection.The Förster resonance energy transfer based upconversion nanoparticles(UCNPs)-graphene oxide sensor offers highly selective and sensitive detection of NP in linear ranges of 5−200 ng/mL and 200−1000 ng/mL under 980 nm and 808 nm excitation,respectively,with LOD at 4.2 ng/mL.The sensors were successfully tested for NP detection in real liquid milk samples with excellent recovery results.The rare-earth fluoride based upconversion luminescence nanosensor with NIR excitation wavelength,holds promise for sensing food,environmental,and biological samples due to their high sensitivity,specific recognition,low LOD,negligible autofluorescence,along with the deep penetration of NIR excitation sources.
基金supported by the Foundation of Equipment Preresearch Area(Grant No.80919010303).
文摘Missile-borne short-range infrared detection(SIRD)technology is commonly used in military ground target detection.In complex battlefield environments,achieving precise strike on ground target is a challenging task.However,real battlefield data is limited,and equivalent experiments are costly.Currently,there is a lack of comprehensive physical modeling and numerical simulation methods for SIRD.To this end,this study proposes a SIRD simulation framework incorporating full-link physical response,which is integrated through the radiative transfer layer,the sensor response layer,and the model-driven layer.In the radiative transfer layer,a coupled dynamic detection model is established to describe the external optical channel response of the SIRD system by combining the infrared radiation model and the geometric measurement model.In the sensor response layer,considering photoelectric conversion and signal processing,the internal signal response model of the SIRD system is established by a hybrid mode of parametric modeling and analog circuit analysis.In the model-driven layer,a cosimulation application based on a three-dimensional virtual environment is proposed to drive the full-link physical model,and a parallel ray tracing method is employed for real-time synchronous simulation.The proposed simulation framework can provide pixel-level signal output and is verified by the measured data.The evaluation results of the root mean square error(RMSE)and the Pearson correlation coefficient(PCC)show that the simulated data and the measured data achieve good consistency,and the evaluation results of the waveform eigenvalues indicate that the simulated signals exhibit low errors compared to the measured signals.The proposed simulation framework has the potential to acquire large sample datasets of SIRD under various complex battlefield environments and can provide an effective data source for SIRD application research.
基金supported by the National Natural Science Foundation of China(62276055).
文摘Ant colony optimization(ACO)is a random search algorithm based on probability calculation.However,the uninformed search strategy has a slow convergence speed.The Bayesian algorithm uses the historical information of the searched point to determine the next search point during the search process,reducing the uncertainty in the random search process.Due to the ability of the Bayesian algorithm to reduce uncertainty,a Bayesian ACO algorithm is proposed in this paper to increase the convergence speed of the conventional ACO algorithm for image edge detection.In addition,this paper has the following two innovations on the basis of the classical algorithm,one of which is to add random perturbations after completing the pheromone update.The second is the use of adaptive pheromone heuristics.Experimental results illustrate that the proposed Bayesian ACO algorithm has faster convergence and higher precision and recall than the traditional ant colony algorithm,due to the improvement of the pheromone utilization rate.Moreover,Bayesian ACO algorithm outperforms the other comparative methods in edge detection task.
