Developing an accurate and visual sensing strategy for trace levels of fluoroquinolone residues that pose threat to food safety and human health is highly desired but remains challenging.Herein,a target selfcalibratio...Developing an accurate and visual sensing strategy for trace levels of fluoroquinolone residues that pose threat to food safety and human health is highly desired but remains challenging.Herein,a target selfcalibration ratiometric fluorescent sensing platform has been designed for sensitive visual detection of levofloxacin(LEV)based on fluorescent europium metal-organic framework(Eu-MOF)probe.Specifically,the Eu-MOF was facilely synthesized via directly mixing Eu^(3+)with 1,10-phenanthroline-2,9-dicarboxylic acid(PDA)ligand at room temperature,which exhibited well-stable red fluorescence at 612 nm.Upon the addition of target LEV,the significant fluorescence quenching from Eu^(3+)was observed owing to the inner filter effect between the Eu-MOF and LEV.While the intrinsic fluorescence for LEV at 462nm was gradually enhanced,thereby realizing the self-calibration ratiometric fluorescence responses to LEV.Through this strategy,LEV can be detected down to 27 nmol/L.Furthermore,a test paper-based Eu-MOF integrated with the smartphone assisted RGB color analysis was exploited for the quantitative monitoring of LEV through the multi-color changes from red to blue,thus achieved portable,convenient and visual detection of LEV in honey and milk samples.Therefore,the developed strategy could provide a useful tool for supporting the practical on-site test in food samples.展开更多
We developed a fluorescent double network hydrogel with ionic responsiveness and high mechanical properties for visual detection.The nanocomposite hydrogel of laponite and polyacrylamide serves as the first network,wh...We developed a fluorescent double network hydrogel with ionic responsiveness and high mechanical properties for visual detection.The nanocomposite hydrogel of laponite and polyacrylamide serves as the first network,while the ionic cross-linked hydrogel of terbium ions and sodium alginate serves as the second network.The double-network structure,the introduction of nanoparticles and the reversible ionic crosslinked interactions confer high mechanical properties to the hydrogel.Terbium ions are not only used as the ionic cross-linked points,but also used as green emitters to endow hydrogels with fluorescent properties.On the basis of the “antenna effect” of terbium ions and the ion exchange interaction,the fluorescence of the hydrogels can make selective responses to various ions(such as organic acid radical ions,transition metal ions) in aqueous solutions,which enables a convenient strategy for visual detection toward ions.Consequently,the fluorescent double network hydrogel fabricated in this study is promising for use in the field of visual sensor detection.展开更多
The multi-level modeling technology of Building Information Modeling(BIM),combined with Three-dimensional Geographic Information System(3DGIS)macro-scene visualization technology and location information,can realize t...The multi-level modeling technology of Building Information Modeling(BIM),combined with Three-dimensional Geographic Information System(3DGIS)macro-scene visualization technology and location information,can realize the transmission of decentralized information from various disciplines to multi-disciplinary collaborative information sharing services.It can be applied independently for the whole life cycle,which plays a positive role in reducing the cost and improving the efficiency of engineering planning,design,construction,operation,and maintenance.In this paper,the data integration and function integration methods of 3DGIS and BIM are designed.In order to avoid the breaking problems caused by attribute information loss and excessive simplification in the process of BIM data integration,the attribute mapping between 3DGIS and BIM based on Industry Foundation Classes(IFC)and City Geography Markup Language(CityGML)and the data simplification method considering the geometric characteristics of BIM are designed.By setting the relevant preconditions and thresholds of patch merging,on the premise of maintaining the structural characteristics of BIM data surface,reduce the amount of model data to improve the efficiency of BIM data loading,rendering and display effect in 3D geospatial scene.Through the data and function integration of 3DGIS and BIM,we can effectively manage the data of large-scale model,and calculate and obtain the geospatial location and direction of key parts of buildings through the coordinate transformation of BIM,which can effectively assist the rapid and accurate positioning of BIM in virtual 3D scene and expand the visualization ability of 3DGIS.By effectively integrating 3DGIS and BIM,this paper gives full play to the spatial management advantages of 3DGIS and the component management advantages of BIM.The rationality and operability of the method are verified by its application in the operation and maintenance management project of concealed facilities in actual buildings.展开更多
Objective To establish an ultra-sensitive,ultra-fast,visible detection method for Vibrio parahaemolyticus(VP).Methods We established a new method for detecting the tdh and trh genes of VP using clustered regularly int...Objective To establish an ultra-sensitive,ultra-fast,visible detection method for Vibrio parahaemolyticus(VP).Methods We established a new method for detecting the tdh and trh genes of VP using clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 12a(CRISPR/Cas12a)combined with recombinase polymerase amplification and visual detection(CRISPR/Cas12a-VD).Results CRISPR/Cas12a-VD accurately detected target DNA at concentrations as low as 10^(-18)M(single molecule detection)within 30 min without cross-reactivity against other bacteria.When detecting pure cultures of VP,the consistency of results reached 100%compared with real-time PCR.The method accurately analysed pure cultures and spiked shrimp samples at concentrations as low as 10^(2)CFU/g.Conclusion The novel CRISPR/Cas12a-VD method for detecting VP performed better than traditional detection methods,such as real-time PCR,and has great potential for preventing the spread of pathogens.展开更多
The rapid and sensitive detection of 2,6-pyridinedicarboxylic acid(DPA),one of the main biomarkers of Bacillus anthracis,is of great significance for the screening and diagnosing of anthrax.Herein,a ratiometric fluore...The rapid and sensitive detection of 2,6-pyridinedicarboxylic acid(DPA),one of the main biomarkers of Bacillus anthracis,is of great significance for the screening and diagnosing of anthrax.Herein,a ratiometric fluorescent nanoprobe based on zeolite imidazolate framework-8(ZIF-8)@AuNCs-Tb was constructed by embedding both gold nanoclusters(AuNCs)and terbium ions(Tb^(3+))into ZIF-8 for highresolution visual detection of DPA.Due to the aggregation induced emission enhancement(AIE)effect,AuNCs embedded in ZIF-8 emit a strong orange fluorescence.When Tb^(3+)is coordinated with DPA added to the nanoprobe,it will emit a strong green fluorescence owing to the antenna effect.The results reveal that ZIF-8@AuNCs-Tb nanoprobe can detect DPA effectively with a good linear relationship in the range of 40-200 and 200-1000μmol/L,the limit of detection(LOD)is estimated at 1.8μmol/L(3σ/k).The proposed nanoprobe shows a remarkable selectivity for DPA and is quite easy to realize visualization based on the fluorescent color changing from orange to green,which has potential application in clinical diagnosis.The feasibility of this method was verified by standard addition recovery experiments simulating the release of DPA from spores.展开更多
Microbially contaminated food can cause serious health hazards and economic losses,therefore sensitive,rapid,and highly specific visual detection is called for.Traditional detection of microorganisms is complex and ti...Microbially contaminated food can cause serious health hazards and economic losses,therefore sensitive,rapid,and highly specific visual detection is called for.Traditional detection of microorganisms is complex and time-consuming,which cannot meet current testing demands.The emergence of paper-based biosensors provided an effective method for efficient and visual detection of microorganisms,due to its high speed,all-in-one device,low cost,and convenience.This review focused on 5 biomarkers,namely nucleic acids,proteins,lipopolysaccharides.metabolites,and the whole microorganism of microorganisms.Besides,the recognition methods were summed up in 5 forms,including immunological recognition,aptamer recognition,nucleic acid amplification-mediated recognition.DNAzyme recognition and clustered regularly interspaced short palindromic repeats mediated recognition.In addition,we summarized the applications of paper-based biosensors in the detection of microorganisms thoroughly.Through the exploration of different biomarkers,identification methods,and applications,we hope to provide a reference for the development of paper-based biosensors and their application in safeguarding the food chain.展开更多
Herein we report the facial detection of formaldehyde(FA)by using an interesting red acidichromic carbon dots(ACDs)which turns blue when pH gradually decreases.The color change was attributed to the conversion between...Herein we report the facial detection of formaldehyde(FA)by using an interesting red acidichromic carbon dots(ACDs)which turns blue when pH gradually decreases.The color change was attributed to the conversion between the double bonds(C=N)and single bonds(C-N)on the surface of the ACDs.Inspired by the reaction between FA and ammonium chloride that produces H^(+)and methenamine and decrease the pH value of the solution,a fast and simple visual detection method for FA was found with a minimum discriminated concentration of 0.04 mol/L.A fluorescence detection method for FA was also found with LOD of 0.029 mol/L and FA in real sample,e.g.,shredded squid was successfully analyzed.This work provides a new idea of developing fast visual detection method for daily monitor or in-site semiquantitative assessment on FA.展开更多
The complexity of living environment system demands higher requirements for the sensitivity and selectivity of the probe.Therefore,it is of great importance to develop a universal strategy for highperformance probe op...The complexity of living environment system demands higher requirements for the sensitivity and selectivity of the probe.Therefore,it is of great importance to develop a universal strategy for highperformance probe optimization.Herein,we propose a novel“Enrichment-enhanced Detection”strategy and use carbon dots-dopamine detection system as a representative model to evaluate its feasibility.The composite probe carbon dots (CDs)-encapsulated in glycol-chitosan (GC)(i.e.,CDs@GC) was obtained by simply mixing GC and CDs through noncovalent interactions,including electrostatic interactions and hydrogen bonding.Dopamine (DA) could be detected through internal filter effect (IFE)-induced quenching of CDs.In the case of CDs@GC,noncovalent interactions (electrostatic interactions) between GC and the formed quinone (oxide of DA) could selectively extract and enrich the local concentration of DA,thus effectively improving the sensitivity and selectivity of the sensing system.The nanosensor had a low detection limit of 3.7 nmol/L,which was a 12-fold sensitivity improvement compared to the bare CDs probes with similar fluorescent profiles,proving the feasibility of the“Enrichment-enhanced Detection”strategy.Further,to examine this theory in real case,we designed a highly portable sensing platform to realize visual determination of DA.Overall,our work introduces a new strategy for accurately detecting DA and provides valuable insights for the universal design and optimization of superior nanoprobes.展开更多
The organic fluorescent probes were widely explored for specific detection of chemical nerve agent simulants.However,the fluorescence quenching,long-time response,and limitation of detection further impeded their prac...The organic fluorescent probes were widely explored for specific detection of chemical nerve agent simulants.However,the fluorescence quenching,long-time response,and limitation of detection further impeded their practical applications.Herein,the fluorescent nanofiber chitosan-1 was prepared through the modification of chitosan with 1,8-naphthalimide as fluorophore and piperazine as the detection segment.The high specific surface of fluorescent nanofiber chitosan-1 showed ultrasensitive and selective detection of diethyl chlorophosphate(DCP)in solution and vapor.The satisfied linear relationship between the fluorescent intensity and the concentration of DCP ranging from 0μmol/L to 100μmol/L was obtained.The limitation of detection was measured as low as 2.2 nmol/L within 30 s.The sensing mechanism was explored through the photoinduced electron transfer(PET)mechanism which was confirmed by ^(1)H,^(31)P NMR,and mass spectra(MS).The ultrasensitive detection of nanofibers may provide valuable insights for enhancing the sensing performance in visually detecting chemical nerve agents.展开更多
There is a growing need for protective instruments that can be used in extreme environments,including those encountered during exoplanet exploration,anti-terrorism activities,and in chemical plants.These instruments s...There is a growing need for protective instruments that can be used in extreme environments,including those encountered during exoplanet exploration,anti-terrorism activities,and in chemical plants.These instruments should have the ability to detect external threats visually and monitor internal physiological signals in real time for maximum safety.To address this need,multifunctional semiconducting fibers with visual detection ranging from yellow to red and near-field communication(NFC)capabilities have been developed for use in personal protective clothing.A composite conductive yarn with semiconducting fluorescent probe molecules is embroidered on the clothing,forming an NFC coil that allows for the visual monitoring of atmospheric safety through color changes.The fluorescence detection system was able to selectively detect diethyl chlorophosphate(DCP),a substitute for the toxic gas sarin,with a detection limit of 6.08 ppb,which is lower than the life-threatening concentration of sarin gas.Furthermore,an intelligent protective suit with the abovementioned dual functions was fabricated with good mechanical cycle stability and repeatability.Real-time physiological signals such as the temperature and humidity of the wearer could be read through the NFC conveniently.Such intelligent protective suits can quickly provide an early warning to the identified low-dose DCP and evaluate the health of wearer according to the changes in physiological signals.This study offers a smart,low-cost strategy for designing intelligent protective devices for extreme environments.展开更多
In the recent COVID-19 pandemic,World Health Organization emphasized that early detection is an effective strategy to reduce the spread of SARS-CoV-2 viruses.Several diagnostic methods,such as reverse transcription-po...In the recent COVID-19 pandemic,World Health Organization emphasized that early detection is an effective strategy to reduce the spread of SARS-CoV-2 viruses.Several diagnostic methods,such as reverse transcription-polymerase chain reaction(RT-PCR)and lateral flow immunoassay(LFIA),have been applied based on the mechanism of specific recognition and binding of the probes to viruses or viral antigens.Although the remarkable progress,these methods still suffer from inadequate cellular materials or errors in the detection and sampling procedure of nasopharyngeal/oropharyngeal swab collection.Therefore,developing accurate,ultrafast,and visualized detection calls for more advanced materials and technology urgently to fight against the epidemic.In this review,we first summarize the current methodologies for SARS-CoV-2 diagnosis.Then,recent representative examples are introduced based on various output signals(e.g.,colorimetric,fluorometric,electronic,acoustic).Finally,we discuss the limitations of the methods and provide our perspectives on priorities for future test development.展开更多
In the present study, we developed a highly sensitive and convenient biosensor consisting of gold nanoparticle （AuNP） probes and a gene chip to detect microRNAs （miRNAs）. Specific oligonucleotides were attached to...In the present study, we developed a highly sensitive and convenient biosensor consisting of gold nanoparticle （AuNP） probes and a gene chip to detect microRNAs （miRNAs）. Specific oligonucleotides were attached to the glass surface as capture probes for the target miRNAs, which were then detected via hybridization to the AuNP probes. The signal was amplified via the re- duction of HAuCI4 by H202. The use of a single AuNP probe detected 10 pmol L-1 of target miRNA. The recovery rate for miR-126 from fetal bovine serum was 81.5%-109.1%. The biosensor detection of miR-126 in total RNA extracted from lung cancer tissues was consistent with the quantitative PCR （qPCR） results. The use of two AuNP probes further improved the de- tection sensitivity such that even 1 fmol L-t of target miR-125a-5p was detectable. This assay takes less than 1 h to complete and the results can be observed by the naked eye, The platform simultaneously detected lung cancer related miR-126 and miR-125a-5p. Therefore, this low cost, rapid, and convenient technology could be used for ultrasensitive and robust visual miRNA detection.展开更多
Subway tunnels often suffer from surface pathologies such as cracks,corrosion,fractures,peeling,water and sand infiltration,and sudden hazards caused by foreign object intrusions.Installing a mobile visual pathology s...Subway tunnels often suffer from surface pathologies such as cracks,corrosion,fractures,peeling,water and sand infiltration,and sudden hazards caused by foreign object intrusions.Installing a mobile visual pathology sensing system at the front end of operating trains is a critical measure to ensure subway safety.Taking leakage as the typical pathology,a tunnel pathology automatic visual detection method based on Deeplabv3+(ASTPDS)was proposed to achieve automatic and high-precision detection and pixel-level morphology extraction of pathologies.Compared with similar methods,this approach showed significant advantages and achieved a detection accuracy of 93.12%,surpassing FCN and U-Net.Moreover,it also exceeded the recall rates for detecting leaks of FCN and U-Net by 8.33%and 8.19%,respectively.展开更多
With the rapid development of automated visual analysis,visual analysis systems have become a popular research topic in the field of computer vision and automated analysis.Visual analysis systems can assist humans to ...With the rapid development of automated visual analysis,visual analysis systems have become a popular research topic in the field of computer vision and automated analysis.Visual analysis systems can assist humans to detect anomalous events(e.g.,fighting,walking alone on the grass,etc).In general,the existing methods for visual anomaly detection are usually based on an autoencoder architecture,i.e.,reconstructing the current frame or predicting the future frame.Then,the reconstruction error is adopted as the evaluation metric to identify whether an input is abnormal or not.The flaws of the existing methods are that abnormal samples can also be reconstructed well.In this paper,inspired by the human memory ability,we propose a novel deep neural network(DNN)based model termed cognitive memory-augmented network(CMAN)for the visual anomaly detection problem.The proposed CMAN model assumes that the visual analysis system imitates humans to remember normal samples and then distinguishes abnormal events from the collected videos.Specifically,in the proposed CMAN model,we introduce a memory module that is able to simulate the memory capacity of humans and a density estimation network that can learn the data distribution.The reconstruction errors and the novelty scores are used to distinguish abnormal events from videos.In addition,we develop a two-step scheme to train the proposed model so that the proposed memory module and the density estimation network can cooperate to improve performance.Comprehensive experiments evaluated on various popular benchmarks show the superiority and effectiveness of the proposed CMAN model for visual anomaly detection comparing with the state-of-the-arts methods.The implementation code of our CMAN method can be accessed at https://github.com/CMANcode/CMAN_pytorch.展开更多
Visual fire detection technologies can detect fire and alarm warnings earlier than conventional fire detectors. This study proposes an effective visual fire detection method that combines the statistical fire color mo...Visual fire detection technologies can detect fire and alarm warnings earlier than conventional fire detectors. This study proposes an effective visual fire detection method that combines the statistical fire color model and sequential pattern mining technology to detect fire in an image. Furthermore, the proposed method also supports real-time fire detection by integrating adaptive background subtraction technologies. Experimental results show that the proposed method can effectively detect fire in test images and videos. The detection accuracy of the proposed hybrid method is better than that of Celik＇s method.展开更多
During mine filling,the caking in the pipeline and the waste rock in the filling slurry may cause serious safety accidents such as pipe blocking or explosion.Therefore,the visualization of the innermine filling of the...During mine filling,the caking in the pipeline and the waste rock in the filling slurry may cause serious safety accidents such as pipe blocking or explosion.Therefore,the visualization of the innermine filling of the solid-liquid two-phase flow in the pipeline is important.This paper proposes a method based on capacitance tomography for the visualization of the solid-liquid distribution on the section of a filling pipe.A feedback network is used for electrical capacitance tomography reconstruction.This reconstruction method uses radial basis function neural network fitting to determine the relationship between the capacitance vector and medium distribution error.In the reconstruction process,the error in the linear back projection is removed;thus,the reconstruction problem becomes an accurate linear problem.The simulation results showthat the reconstruction accuracy of this algorithm is better than that of many traditional algorithms;furthermore,the reconstructed image artifacts are fewer,and the phase distribution boundary is clearer.This method can help determine the location and size of the caking and waste rock in the cross section of the pipeline more accurately and has great application prospects in the visualization of filling pipelines in mines.展开更多
Traditional vehicle detection algorithms use traverse search based vehicle candidate generation and hand crafted based classifier training for vehicle candidate verification.These types of methods generally have high ...Traditional vehicle detection algorithms use traverse search based vehicle candidate generation and hand crafted based classifier training for vehicle candidate verification.These types of methods generally have high processing times and low vehicle detection performance.To address this issue,a visual saliency and deep sparse convolution hierarchical model based vehicle detection algorithm is proposed.A visual saliency calculation is firstly used to generate a small vehicle candidate area.The vehicle candidate sub images are then loaded into a sparse deep convolution hierarchical model with an SVM-based classifier to perform the final detection.The experimental results demonstrate that the proposed method is with 94.81% correct rate and 0.78% false detection rate on the existing datasets and the real road pictures captured by our group,which outperforms the existing state-of-the-art algorithms.More importantly,high discriminative multi-scale features are generated by deep sparse convolution network which has broad application prospects in target recognition in the field of intelligent vehicle.展开更多
In this study,a simple and effective ratiometric fluorescence method has been developed for carbaryl detection,utilizing red emissive carbon dots(R-CDs).The underlying principle of this proposed strategy relies on the...In this study,a simple and effective ratiometric fluorescence method has been developed for carbaryl detection,utilizing red emissive carbon dots(R-CDs).The underlying principle of this proposed strategy relies on the rapid hydrolysis of carbaryl under an alkaline condition and production of 1-naphthol with blue-emission at 462 nm.Furthermore,the as-synthesized R-CDs(Em.677 nm),serve as a reference,enhancing the visual tracking of carbaryl through the transformation of fluorescent color from red to blue.The concentration of carbaryl exhibits a commendable linear correlation with the ratio of fluorescence intensity,ranging from 0 to 20μg/m L(R^(2)=0.9989)with a low detection limit of 0.52 ng/m L.Additionally,the described methodology can be used for the enzyme-free visual assay of carbaryl,even in the presence of other carbamate pesticides and metal ions,in tap water and lake water samples with excellent accuracy(spiked recoveries,94%-106.1%),high precision(relative standard deviation(RSD)≤2.42),and remarkable selectivity.This fast and highly sensitive naked-eye ratiometric sensor holds immense promise for carbaryl detection in intricate environments and food safety fields.展开更多
A ceramic ball is a basic part widely used in precision bearings.There is no perfect testing equipment for ceramic ball surface defects at present.A fast visual detection algorithm for ceramic ball surface defects bas...A ceramic ball is a basic part widely used in precision bearings.There is no perfect testing equipment for ceramic ball surface defects at present.A fast visual detection algorithm for ceramic ball surface defects based on fringe reflection is designed.By means of image preprocessing,grayscale value accumulative differential positioning,edge detection,pixel-value row difference and template matching,the algorithm can locate feature points and judge whether the spherical surface has defects by the number of points.Taking black silicon nitride ceramic balls with a diameter of 6.35 mm as an example,the defect detection time for a single gray scale image is 0.78 s,and the detection limit is 16.5μm.展开更多
An integration processing system of three-dimensional laser scanning information visualization in goaf was developed. It is provided with multiple functions, such as laser scanning information management for goaf, clo...An integration processing system of three-dimensional laser scanning information visualization in goaf was developed. It is provided with multiple functions, such as laser scanning information management for goaf, cloud data de-noising optimization, construction, display and operation of three-dimensional model, model editing, profile generation, calculation of goaf volume and roof area, Boolean calculation among models and interaction with the third party soft ware. Concerning this system with a concise interface, plentiful data input/output interfaces, it is featured with high integration, simple and convenient operations of applications. According to practice, in addition to being well-adapted, this system is favorably reliable and stable.展开更多
基金supported by the National Natural Science Foundation of China(Nos.32260247 and 22064010)the Natural Science Foundation of Jiangxi Province(Nos.20232BAB215071 and 20224BAB213009).
文摘Developing an accurate and visual sensing strategy for trace levels of fluoroquinolone residues that pose threat to food safety and human health is highly desired but remains challenging.Herein,a target selfcalibration ratiometric fluorescent sensing platform has been designed for sensitive visual detection of levofloxacin(LEV)based on fluorescent europium metal-organic framework(Eu-MOF)probe.Specifically,the Eu-MOF was facilely synthesized via directly mixing Eu^(3+)with 1,10-phenanthroline-2,9-dicarboxylic acid(PDA)ligand at room temperature,which exhibited well-stable red fluorescence at 612 nm.Upon the addition of target LEV,the significant fluorescence quenching from Eu^(3+)was observed owing to the inner filter effect between the Eu-MOF and LEV.While the intrinsic fluorescence for LEV at 462nm was gradually enhanced,thereby realizing the self-calibration ratiometric fluorescence responses to LEV.Through this strategy,LEV can be detected down to 27 nmol/L.Furthermore,a test paper-based Eu-MOF integrated with the smartphone assisted RGB color analysis was exploited for the quantitative monitoring of LEV through the multi-color changes from red to blue,thus achieved portable,convenient and visual detection of LEV in honey and milk samples.Therefore,the developed strategy could provide a useful tool for supporting the practical on-site test in food samples.
基金Funded by the National Natural Science Foundation of China(No.51873167)the National Innovation and Entrepreneurship Training Program for College Students(No.226801001)。
文摘We developed a fluorescent double network hydrogel with ionic responsiveness and high mechanical properties for visual detection.The nanocomposite hydrogel of laponite and polyacrylamide serves as the first network,while the ionic cross-linked hydrogel of terbium ions and sodium alginate serves as the second network.The double-network structure,the introduction of nanoparticles and the reversible ionic crosslinked interactions confer high mechanical properties to the hydrogel.Terbium ions are not only used as the ionic cross-linked points,but also used as green emitters to endow hydrogels with fluorescent properties.On the basis of the “antenna effect” of terbium ions and the ion exchange interaction,the fluorescence of the hydrogels can make selective responses to various ions(such as organic acid radical ions,transition metal ions) in aqueous solutions,which enables a convenient strategy for visual detection toward ions.Consequently,the fluorescent double network hydrogel fabricated in this study is promising for use in the field of visual sensor detection.
基金supported by the Open Fund of Key Laboratory of Urban Land Resources Monitoring and Simulation,Ministry of Land and Resources[grant number KF-2018-03-050]China Postdoctoral Science Foundation[grant number 2018M642800].
文摘The multi-level modeling technology of Building Information Modeling(BIM),combined with Three-dimensional Geographic Information System(3DGIS)macro-scene visualization technology and location information,can realize the transmission of decentralized information from various disciplines to multi-disciplinary collaborative information sharing services.It can be applied independently for the whole life cycle,which plays a positive role in reducing the cost and improving the efficiency of engineering planning,design,construction,operation,and maintenance.In this paper,the data integration and function integration methods of 3DGIS and BIM are designed.In order to avoid the breaking problems caused by attribute information loss and excessive simplification in the process of BIM data integration,the attribute mapping between 3DGIS and BIM based on Industry Foundation Classes(IFC)and City Geography Markup Language(CityGML)and the data simplification method considering the geometric characteristics of BIM are designed.By setting the relevant preconditions and thresholds of patch merging,on the premise of maintaining the structural characteristics of BIM data surface,reduce the amount of model data to improve the efficiency of BIM data loading,rendering and display effect in 3D geospatial scene.Through the data and function integration of 3DGIS and BIM,we can effectively manage the data of large-scale model,and calculate and obtain the geospatial location and direction of key parts of buildings through the coordinate transformation of BIM,which can effectively assist the rapid and accurate positioning of BIM in virtual 3D scene and expand the visualization ability of 3DGIS.By effectively integrating 3DGIS and BIM,this paper gives full play to the spatial management advantages of 3DGIS and the component management advantages of BIM.The rationality and operability of the method are verified by its application in the operation and maintenance management project of concealed facilities in actual buildings.
基金supported by the National Key Research and Development Plan of China[2018YFC1602500]the Natural Science Foundation of Tianjin[19JCZDJC39900]
文摘Objective To establish an ultra-sensitive,ultra-fast,visible detection method for Vibrio parahaemolyticus(VP).Methods We established a new method for detecting the tdh and trh genes of VP using clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 12a(CRISPR/Cas12a)combined with recombinase polymerase amplification and visual detection(CRISPR/Cas12a-VD).Results CRISPR/Cas12a-VD accurately detected target DNA at concentrations as low as 10^(-18)M(single molecule detection)within 30 min without cross-reactivity against other bacteria.When detecting pure cultures of VP,the consistency of results reached 100%compared with real-time PCR.The method accurately analysed pure cultures and spiked shrimp samples at concentrations as low as 10^(2)CFU/g.Conclusion The novel CRISPR/Cas12a-VD method for detecting VP performed better than traditional detection methods,such as real-time PCR,and has great potential for preventing the spread of pathogens.
基金Project supported by the National Natural Science Foundation of China(21804119)Natural Science Foundation of Zhejiang Province(LZ18B050002)Natural Science Foundation of Hubei Province(2018CFB388)。
文摘The rapid and sensitive detection of 2,6-pyridinedicarboxylic acid(DPA),one of the main biomarkers of Bacillus anthracis,is of great significance for the screening and diagnosing of anthrax.Herein,a ratiometric fluorescent nanoprobe based on zeolite imidazolate framework-8(ZIF-8)@AuNCs-Tb was constructed by embedding both gold nanoclusters(AuNCs)and terbium ions(Tb^(3+))into ZIF-8 for highresolution visual detection of DPA.Due to the aggregation induced emission enhancement(AIE)effect,AuNCs embedded in ZIF-8 emit a strong orange fluorescence.When Tb^(3+)is coordinated with DPA added to the nanoprobe,it will emit a strong green fluorescence owing to the antenna effect.The results reveal that ZIF-8@AuNCs-Tb nanoprobe can detect DPA effectively with a good linear relationship in the range of 40-200 and 200-1000μmol/L,the limit of detection(LOD)is estimated at 1.8μmol/L(3σ/k).The proposed nanoprobe shows a remarkable selectivity for DPA and is quite easy to realize visualization based on the fluorescent color changing from orange to green,which has potential application in clinical diagnosis.The feasibility of this method was verified by standard addition recovery experiments simulating the release of DPA from spores.
基金This research was supported by Beijing Innovation Consortium of Agriculture Research System(BAIC09-2022)Young Elite Scientist Sponsorship Program Bybast(BYESS2022133)。
文摘Microbially contaminated food can cause serious health hazards and economic losses,therefore sensitive,rapid,and highly specific visual detection is called for.Traditional detection of microorganisms is complex and time-consuming,which cannot meet current testing demands.The emergence of paper-based biosensors provided an effective method for efficient and visual detection of microorganisms,due to its high speed,all-in-one device,low cost,and convenience.This review focused on 5 biomarkers,namely nucleic acids,proteins,lipopolysaccharides.metabolites,and the whole microorganism of microorganisms.Besides,the recognition methods were summed up in 5 forms,including immunological recognition,aptamer recognition,nucleic acid amplification-mediated recognition.DNAzyme recognition and clustered regularly interspaced short palindromic repeats mediated recognition.In addition,we summarized the applications of paper-based biosensors in the detection of microorganisms thoroughly.Through the exploration of different biomarkers,identification methods,and applications,we hope to provide a reference for the development of paper-based biosensors and their application in safeguarding the food chain.
基金support from the National Natural Science Foundation of China(Nos.21804062,52071171,and 52202248)Liaoning BaiQianWan Talents Program(No.LNBQW2018B0048)+8 种基金Shenyang Science and Technology Project(No.21-108-9-04)Key Research Project of Department of Education of Liaoning Province(No.LJKZZ20220015)Australian Research Council(ARC)through Future Fellowship(No.FT210100298)Discovery Project(No.DP220100603)Linkage Project(Nos.LP210200504,LP220100088,and LP230200897)Industrial Transformation Research Hub(No.IH240100009)schemesthe Australian Government through the Cooperative Research Centres Projects(No.CRCPXIII000077)the Australian Renewable Energy Agency(ARENA)as part of ARENA’s Transformative Research Accelerating Commercialisation Program(No.TM021)European Commission’s Australia-Spain Network for Innovation and Research Excellence(AuSpire).
文摘Herein we report the facial detection of formaldehyde(FA)by using an interesting red acidichromic carbon dots(ACDs)which turns blue when pH gradually decreases.The color change was attributed to the conversion between the double bonds(C=N)and single bonds(C-N)on the surface of the ACDs.Inspired by the reaction between FA and ammonium chloride that produces H^(+)and methenamine and decrease the pH value of the solution,a fast and simple visual detection method for FA was found with a minimum discriminated concentration of 0.04 mol/L.A fluorescence detection method for FA was also found with LOD of 0.029 mol/L and FA in real sample,e.g.,shredded squid was successfully analyzed.This work provides a new idea of developing fast visual detection method for daily monitor or in-site semiquantitative assessment on FA.
基金the financial support from the National Natural Science Foundation of China(No.21904007)the Fundamental Research Funds for the Central Universities(China,No.2412022QD008)+1 种基金the Jilin Provincial Department of Education(China),the Key Laboratory of Nanobiosensing and Nanobioanalysis at Universities of Jilin Province(China)the Analysis and Testing Center of Northeast Normal University(China)。
文摘The complexity of living environment system demands higher requirements for the sensitivity and selectivity of the probe.Therefore,it is of great importance to develop a universal strategy for highperformance probe optimization.Herein,we propose a novel“Enrichment-enhanced Detection”strategy and use carbon dots-dopamine detection system as a representative model to evaluate its feasibility.The composite probe carbon dots (CDs)-encapsulated in glycol-chitosan (GC)(i.e.,CDs@GC) was obtained by simply mixing GC and CDs through noncovalent interactions,including electrostatic interactions and hydrogen bonding.Dopamine (DA) could be detected through internal filter effect (IFE)-induced quenching of CDs.In the case of CDs@GC,noncovalent interactions (electrostatic interactions) between GC and the formed quinone (oxide of DA) could selectively extract and enrich the local concentration of DA,thus effectively improving the sensitivity and selectivity of the sensing system.The nanosensor had a low detection limit of 3.7 nmol/L,which was a 12-fold sensitivity improvement compared to the bare CDs probes with similar fluorescent profiles,proving the feasibility of the“Enrichment-enhanced Detection”strategy.Further,to examine this theory in real case,we designed a highly portable sensing platform to realize visual determination of DA.Overall,our work introduces a new strategy for accurately detecting DA and provides valuable insights for the universal design and optimization of superior nanoprobes.
基金financial support from the National Natural Science Foundation of China(Nos.82104065,32061143045,22276142,22474003)the National Key Research&Development Program(Nos.2019YFE0123100,2022YFE0199800)+2 种基金Anhui Provincial Natural Science Foundation(No.2208085MB38)Anhui Provincial Natural Science Foundation for Distinguished Young Scholars(No.2008085J11)Foundation of Education Department of Anhui Province(No.2022AH010023).
文摘The organic fluorescent probes were widely explored for specific detection of chemical nerve agent simulants.However,the fluorescence quenching,long-time response,and limitation of detection further impeded their practical applications.Herein,the fluorescent nanofiber chitosan-1 was prepared through the modification of chitosan with 1,8-naphthalimide as fluorophore and piperazine as the detection segment.The high specific surface of fluorescent nanofiber chitosan-1 showed ultrasensitive and selective detection of diethyl chlorophosphate(DCP)in solution and vapor.The satisfied linear relationship between the fluorescent intensity and the concentration of DCP ranging from 0μmol/L to 100μmol/L was obtained.The limitation of detection was measured as low as 2.2 nmol/L within 30 s.The sensing mechanism was explored through the photoinduced electron transfer(PET)mechanism which was confirmed by ^(1)H,^(31)P NMR,and mass spectra(MS).The ultrasensitive detection of nanofibers may provide valuable insights for enhancing the sensing performance in visually detecting chemical nerve agents.
基金support from the Fundamental Research Funds for the Central Universities(Nos.2232020A-03,and 2232021G-12)the National Natural Science Foundation of China(Grant No.52003049,and 62022085)+1 种基金the Science and Technology Commission of Shanghai Municipality(Nos.21520710700)We would also like to express our thanks to Jianxin Liu from Shanghai Feiju Microelectronics Co.,Ltd.for his technical assistance,and Prof.Wei Xu for his helpful discussions in theoretical calculation.
文摘There is a growing need for protective instruments that can be used in extreme environments,including those encountered during exoplanet exploration,anti-terrorism activities,and in chemical plants.These instruments should have the ability to detect external threats visually and monitor internal physiological signals in real time for maximum safety.To address this need,multifunctional semiconducting fibers with visual detection ranging from yellow to red and near-field communication(NFC)capabilities have been developed for use in personal protective clothing.A composite conductive yarn with semiconducting fluorescent probe molecules is embroidered on the clothing,forming an NFC coil that allows for the visual monitoring of atmospheric safety through color changes.The fluorescence detection system was able to selectively detect diethyl chlorophosphate(DCP),a substitute for the toxic gas sarin,with a detection limit of 6.08 ppb,which is lower than the life-threatening concentration of sarin gas.Furthermore,an intelligent protective suit with the abovementioned dual functions was fabricated with good mechanical cycle stability and repeatability.Real-time physiological signals such as the temperature and humidity of the wearer could be read through the NFC conveniently.Such intelligent protective suits can quickly provide an early warning to the identified low-dose DCP and evaluate the health of wearer according to the changes in physiological signals.This study offers a smart,low-cost strategy for designing intelligent protective devices for extreme environments.
基金This work was partially supported by the National Key Research and Development Program of China(2021YFA1201301/2021YFA1201300)Science and Technology Commission of Shanghai Municipality(20JC1414900,19ZR1470600).
文摘In the recent COVID-19 pandemic,World Health Organization emphasized that early detection is an effective strategy to reduce the spread of SARS-CoV-2 viruses.Several diagnostic methods,such as reverse transcription-polymerase chain reaction(RT-PCR)and lateral flow immunoassay(LFIA),have been applied based on the mechanism of specific recognition and binding of the probes to viruses or viral antigens.Although the remarkable progress,these methods still suffer from inadequate cellular materials or errors in the detection and sampling procedure of nasopharyngeal/oropharyngeal swab collection.Therefore,developing accurate,ultrafast,and visualized detection calls for more advanced materials and technology urgently to fight against the epidemic.In this review,we first summarize the current methodologies for SARS-CoV-2 diagnosis.Then,recent representative examples are introduced based on various output signals(e.g.,colorimetric,fluorometric,electronic,acoustic).Finally,we discuss the limitations of the methods and provide our perspectives on priorities for future test development.
基金supported by the National Basic Research Program of China (2012CB933303)the National Natural Science Foundation of China (61571429, 61571077, 61401442)+2 种基金the Innovation Team of Henan University of Science and Technology (2015XTD003)the Science and Technology Commission of Shanghai Municipality (12441902600, 1402H233900)the Shanghai Clinical Center/Shanghai Xuhui Central Hospital, Chinese Academic of Sciences (BRC2012002)
文摘In the present study, we developed a highly sensitive and convenient biosensor consisting of gold nanoparticle （AuNP） probes and a gene chip to detect microRNAs （miRNAs）. Specific oligonucleotides were attached to the glass surface as capture probes for the target miRNAs, which were then detected via hybridization to the AuNP probes. The signal was amplified via the re- duction of HAuCI4 by H202. The use of a single AuNP probe detected 10 pmol L-1 of target miRNA. The recovery rate for miR-126 from fetal bovine serum was 81.5%-109.1%. The biosensor detection of miR-126 in total RNA extracted from lung cancer tissues was consistent with the quantitative PCR （qPCR） results. The use of two AuNP probes further improved the de- tection sensitivity such that even 1 fmol L-t of target miR-125a-5p was detectable. This assay takes less than 1 h to complete and the results can be observed by the naked eye, The platform simultaneously detected lung cancer related miR-126 and miR-125a-5p. Therefore, this low cost, rapid, and convenient technology could be used for ultrasensitive and robust visual miRNA detection.
文摘Subway tunnels often suffer from surface pathologies such as cracks,corrosion,fractures,peeling,water and sand infiltration,and sudden hazards caused by foreign object intrusions.Installing a mobile visual pathology sensing system at the front end of operating trains is a critical measure to ensure subway safety.Taking leakage as the typical pathology,a tunnel pathology automatic visual detection method based on Deeplabv3+(ASTPDS)was proposed to achieve automatic and high-precision detection and pixel-level morphology extraction of pathologies.Compared with similar methods,this approach showed significant advantages and achieved a detection accuracy of 93.12%,surpassing FCN and U-Net.Moreover,it also exceeded the recall rates for detecting leaks of FCN and U-Net by 8.33%and 8.19%,respectively.
基金the National Natural Science Foundation of China(61976049,62072080,U20B2063)the Fundamental Research Funds for the Central Universities(ZYGX2019Z015)+1 种基金the Sichuan Science and Technology Program,China(2018GZDZX0032,2019ZDZX0008,2019YFG0003,2019YFG0533,2020YFS0057)Dongguan Songshan Lake Introduction Program of Leading Innovative and Entrepreneurial Talents.Recommended by Associate Editor Huimin Lu.
文摘With the rapid development of automated visual analysis,visual analysis systems have become a popular research topic in the field of computer vision and automated analysis.Visual analysis systems can assist humans to detect anomalous events(e.g.,fighting,walking alone on the grass,etc).In general,the existing methods for visual anomaly detection are usually based on an autoencoder architecture,i.e.,reconstructing the current frame or predicting the future frame.Then,the reconstruction error is adopted as the evaluation metric to identify whether an input is abnormal or not.The flaws of the existing methods are that abnormal samples can also be reconstructed well.In this paper,inspired by the human memory ability,we propose a novel deep neural network(DNN)based model termed cognitive memory-augmented network(CMAN)for the visual anomaly detection problem.The proposed CMAN model assumes that the visual analysis system imitates humans to remember normal samples and then distinguishes abnormal events from the collected videos.Specifically,in the proposed CMAN model,we introduce a memory module that is able to simulate the memory capacity of humans and a density estimation network that can learn the data distribution.The reconstruction errors and the novelty scores are used to distinguish abnormal events from videos.In addition,we develop a two-step scheme to train the proposed model so that the proposed memory module and the density estimation network can cooperate to improve performance.Comprehensive experiments evaluated on various popular benchmarks show the superiority and effectiveness of the proposed CMAN model for visual anomaly detection comparing with the state-of-the-arts methods.The implementation code of our CMAN method can be accessed at https://github.com/CMANcode/CMAN_pytorch.
基金supported by National Science Council under Grant No. NSC98-2221-E-218-046
文摘Visual fire detection technologies can detect fire and alarm warnings earlier than conventional fire detectors. This study proposes an effective visual fire detection method that combines the statistical fire color model and sequential pattern mining technology to detect fire in an image. Furthermore, the proposed method also supports real-time fire detection by integrating adaptive background subtraction technologies. Experimental results show that the proposed method can effectively detect fire in test images and videos. The detection accuracy of the proposed hybrid method is better than that of Celik＇s method.
基金This research was supported by the National Natural Science Foundation of China(No.51704229)Outstanding Youth Science Fund of Xi’an University of Science and Technology(No.2018YQ2-01).
文摘During mine filling,the caking in the pipeline and the waste rock in the filling slurry may cause serious safety accidents such as pipe blocking or explosion.Therefore,the visualization of the innermine filling of the solid-liquid two-phase flow in the pipeline is important.This paper proposes a method based on capacitance tomography for the visualization of the solid-liquid distribution on the section of a filling pipe.A feedback network is used for electrical capacitance tomography reconstruction.This reconstruction method uses radial basis function neural network fitting to determine the relationship between the capacitance vector and medium distribution error.In the reconstruction process,the error in the linear back projection is removed;thus,the reconstruction problem becomes an accurate linear problem.The simulation results showthat the reconstruction accuracy of this algorithm is better than that of many traditional algorithms;furthermore,the reconstructed image artifacts are fewer,and the phase distribution boundary is clearer.This method can help determine the location and size of the caking and waste rock in the cross section of the pipeline more accurately and has great application prospects in the visualization of filling pipelines in mines.
基金Supported by National Natural Science Foundation of China(Grant Nos.U1564201,61573171,61403172,51305167)China Postdoctoral Science Foundation(Grant Nos.2015T80511,2014M561592)+3 种基金Jiangsu Provincial Natural Science Foundation of China(Grant No.BK20140555)Six Talent Peaks Project of Jiangsu Province,China(Grant Nos.2015-JXQC-012,2014-DZXX-040)Jiangsu Postdoctoral Science Foundation,China(Grant No.1402097C)Jiangsu University Scientific Research Foundation for Senior Professionals,China(Grant No.14JDG028)
文摘Traditional vehicle detection algorithms use traverse search based vehicle candidate generation and hand crafted based classifier training for vehicle candidate verification.These types of methods generally have high processing times and low vehicle detection performance.To address this issue,a visual saliency and deep sparse convolution hierarchical model based vehicle detection algorithm is proposed.A visual saliency calculation is firstly used to generate a small vehicle candidate area.The vehicle candidate sub images are then loaded into a sparse deep convolution hierarchical model with an SVM-based classifier to perform the final detection.The experimental results demonstrate that the proposed method is with 94.81% correct rate and 0.78% false detection rate on the existing datasets and the real road pictures captured by our group,which outperforms the existing state-of-the-art algorithms.More importantly,high discriminative multi-scale features are generated by deep sparse convolution network which has broad application prospects in target recognition in the field of intelligent vehicle.
基金supported by the Natural Science Foundation of the Science and Technology Department of Jilin Province(No.20220101086JC)。
文摘In this study,a simple and effective ratiometric fluorescence method has been developed for carbaryl detection,utilizing red emissive carbon dots(R-CDs).The underlying principle of this proposed strategy relies on the rapid hydrolysis of carbaryl under an alkaline condition and production of 1-naphthol with blue-emission at 462 nm.Furthermore,the as-synthesized R-CDs(Em.677 nm),serve as a reference,enhancing the visual tracking of carbaryl through the transformation of fluorescent color from red to blue.The concentration of carbaryl exhibits a commendable linear correlation with the ratio of fluorescence intensity,ranging from 0 to 20μg/m L(R^(2)=0.9989)with a low detection limit of 0.52 ng/m L.Additionally,the described methodology can be used for the enzyme-free visual assay of carbaryl,even in the presence of other carbamate pesticides and metal ions,in tap water and lake water samples with excellent accuracy(spiked recoveries,94%-106.1%),high precision(relative standard deviation(RSD)≤2.42),and remarkable selectivity.This fast and highly sensitive naked-eye ratiometric sensor holds immense promise for carbaryl detection in intricate environments and food safety fields.
基金National Science and Technology Major Project of China(No.2016ZX04003001)。
文摘A ceramic ball is a basic part widely used in precision bearings.There is no perfect testing equipment for ceramic ball surface defects at present.A fast visual detection algorithm for ceramic ball surface defects based on fringe reflection is designed.By means of image preprocessing,grayscale value accumulative differential positioning,edge detection,pixel-value row difference and template matching,the algorithm can locate feature points and judge whether the spherical surface has defects by the number of points.Taking black silicon nitride ceramic balls with a diameter of 6.35 mm as an example,the defect detection time for a single gray scale image is 0.78 s,and the detection limit is 16.5μm.
基金Project(51274250)supported by the National Natural Science Foundation of ChinaProject(2012BAK09B02-05)supported by the National Key Technology R&D Program during the 12th Five-year Plan of China
文摘An integration processing system of three-dimensional laser scanning information visualization in goaf was developed. It is provided with multiple functions, such as laser scanning information management for goaf, cloud data de-noising optimization, construction, display and operation of three-dimensional model, model editing, profile generation, calculation of goaf volume and roof area, Boolean calculation among models and interaction with the third party soft ware. Concerning this system with a concise interface, plentiful data input/output interfaces, it is featured with high integration, simple and convenient operations of applications. According to practice, in addition to being well-adapted, this system is favorably reliable and stable.
