Expanding the specific surface area of substrates and carrying out precise surface engineering of imprinted nanocavities are crucial methods for enhancing the identification efficiency of molecularly imprinted polymer...Expanding the specific surface area of substrates and carrying out precise surface engineering of imprinted nanocavities are crucial methods for enhancing the identification efficiency of molecularly imprinted polymers(MIPs).To implement this synergistic strategy,bioinspired surface engineering was used to incorporate dual covalent receptors via precise post-imprinting modifications(PIMs)onto mesoporous silica nanosheets.The prepared sorbents(denoted as‘‘D-PMIPs”)were utilized to improve the specific identification of adenosine 5-monophosphate(AMP).Significantly,the mesoporous silica nanosheets possess a high surface area of approximately 498.73 m^(2)·g^(-1),which facilitates the formation of abundant specific recognition sites in the D-PMIPs.The dual covalent receptors are valuable for estab-lishing the spatial orientation and arrangement of AMP through multiple cooperative interactions.PIMs enable precise site-specific functionalization within the imprinted cavities,leading to the tailor-made formation of complementary binding sites.The maximum number of high-affinity binding sites(Nmax)of the D-PMIPs is 39.99 lmol·g^(-1),which is significantly higher than that of imprinted sorbents with a sin-gle receptor(i.e.,S-BMIPs or S-PMIPs).The kinetic data of the D-PMIPs can be effectively described by a pseudo-second-order model,indicating that the main binding mechanism involves synergistic chemisorption from boronate affinity and the pyrimidine base.This study suggests that using dual cova-lent receptors and PIMs is a reliable approach for creating imprinted sorbents with high selectivity,allow-ing for the controlled engineering of imprinted sites.展开更多
In the field of specific emitter identification(SEI),power amplifiers(PAs)have long been recognized as significant contributors to unintentional modulation characteristics.To enhance signal quality,digital pre-distort...In the field of specific emitter identification(SEI),power amplifiers(PAs)have long been recognized as significant contributors to unintentional modulation characteristics.To enhance signal quality,digital pre-distortion(DPD)techniques are commonly employed in practical applications to mitigate the nonlinear effects of PAs.However,DPD techniques may diminish the distinctive characteristics of individual transmitters,potentially compromising SEI performance.This study investigates the influence of SEI in the presence of DPD applied to PAs.We construct a semi-physical emitter platform using AD9361 and ZYNQ,incorporating memory and non-memory models to emulate an amplification system comprising DPD devices and PAs.Furthermore,we delve into the analysis and evaluation of LMS-based and QRDRLS-based DPD algorithms to ascertain their efficacy in compensating for amplifier nonlinearity.Finally,we conduct a comprehensive set of experiments to demonstrate the adverse impact of DPD techniques on SEI.Our findings demonstrate a direct correlation between the degree of DPD performance and its impact magnitude on SEI,thereby providing a foundational basis for future studies investigating SEI techniques under DPD.展开更多
Extensive experiments suggest that kurtosis-based fingerprint features are effective for specific emitter identification (SEI). Nevertheless, the lack of mechanistic explanation restricts the use of fingerprint featur...Extensive experiments suggest that kurtosis-based fingerprint features are effective for specific emitter identification (SEI). Nevertheless, the lack of mechanistic explanation restricts the use of fingerprint features to a data-driven technique and fur-ther reduces the adaptability of the technique to other datasets. To address this issue, the mechanism how the phase noise of high-frequency oscillators and the nonlinearity of power ampli-fiers affect the kurtosis of communication signals is investigated. Mathematical models are derived for intentional modulation (IM) and unintentional modulation (UIM). Analysis indicates that the phase noise of high-frequency oscillators and the nonlinearity of power amplifiers affect the kurtosis frequency and amplitude, respectively. A novel SEI method based on frequency and ampli-tude of the signal kurtosis (FA-SK) is further proposed. Simula-tion and real-world experiments validate theoretical analysis and also confirm the efficiency and effectiveness of the proposed method.展开更多
Existing specific emitter identification(SEI)methods based on hand-crafted features have drawbacks of losing feature information and involving multiple processing stages,which reduce the identification accuracy of emi...Existing specific emitter identification(SEI)methods based on hand-crafted features have drawbacks of losing feature information and involving multiple processing stages,which reduce the identification accuracy of emitters and complicate the procedures of identification.In this paper,we propose a deep SEI approach via multidimensional feature extraction for radio frequency fingerprints(RFFs),namely,RFFsNet-SEI.Particularly,we extract multidimensional physical RFFs from the received signal by virtue of variational mode decomposition(VMD)and Hilbert transform(HT).The physical RFFs and I-Q data are formed into the balanced-RFFs,which are then used to train RFFsNet-SEI.As introducing model-aided RFFs into neural network,the hybrid-driven scheme including physical features and I-Q data is constructed.It improves physical interpretability of RFFsNet-SEI.Meanwhile,since RFFsNet-SEI identifies individual of emitters from received raw data in end-to-end,it accelerates SEI implementation and simplifies procedures of identification.Moreover,as the temporal features and spectral features of the received signal are both extracted by RFFsNet-SEI,identification accuracy is improved.Finally,we compare RFFsNet-SEI with the counterparts in terms of identification accuracy,computational complexity,and prediction speed.Experimental results illustrate that the proposed method outperforms the counterparts on the basis of simulation dataset and real dataset collected in the anechoic chamber.展开更多
Specific emitter identification can distin-guish individual transmitters by analyzing received signals and extracting inherent features of hard-ware circuits.Feature extraction is a key part of traditional machine lea...Specific emitter identification can distin-guish individual transmitters by analyzing received signals and extracting inherent features of hard-ware circuits.Feature extraction is a key part of traditional machine learning-based methods,but manual extrac-tion is generally limited by prior professional knowl-edge.At the same time,it has been noted that the per-formance of most specific emitter identification meth-ods degrades in the low signal-to-noise ratio(SNR)environments.The deep residual shrinkage network(DRSN)is proposed for specific emitter identification,particularly in the low SNRs.The soft threshold can preserve more key features for the improvement of performance,and an identity shortcut can speed up the training process.We collect signals via the receiver to create a dataset in the actual environments.The DRSN is trained to automatically extract features and imple-ment the classification of transmitters.Experimental results show that DRSN obtains the best accuracy un-der different SNRs and has less running time,which demonstrates the effectiveness of DRSN in identify-ing specific emitters.展开更多
The specific emitter identification （SEI） technique some external feature measurements of the signal. determines the unique emitter of a given signal by using It has recently attracted a great deal of attention beca...The specific emitter identification （SEI） technique some external feature measurements of the signal. determines the unique emitter of a given signal by using It has recently attracted a great deal of attention because many applications can benefit from it. This work addresses the SEI problem using two methods, namely, the normalized visibility graph entropy （NVGE） and the normalized horizontal visibility graph entropy （NHVGE） based on treating emitters as nonlinear dynamical systems. Firstly, the visibility graph （VG） and the horizontal visibility graph （HVG） are used to convert the instantaneous amplitude, phase and frequency of received signals into graphs. Then, based on the information captured by the VG and the HVG, the normalized Shannon entropy （NSE） calculated from the corresponding degree distributions are utilized as the rf fingerprint. Finally, four emitters from the same manufacturer are utilized to evaluate the performance of the two methods. Experimental results demonstrate that both the NHVGE-based method and NVGE-based method are quite effective and they perform much better than the method based on the normalized permutation entropy （NPE） in the case of a small amount of data. The NVGE-based method performs better than the NHVGE-based method since the VG can extract more information than the HVG does. Moreover, our methods do not distinguish between the transient signal and the steady-state signal, making it practical.展开更多
Objective\ To understand the transcription of BamHI L DNA fragment from genome of strong virulent GA strain of Marek′s disease herpesvirus (MDV) in lymphoblastoid tumor tissue induced by oncogenic strain Beijing 1 ...Objective\ To understand the transcription of BamHI L DNA fragment from genome of strong virulent GA strain of Marek′s disease herpesvirus (MDV) in lymphoblastoid tumor tissue induced by oncogenic strain Beijing 1 (a specific local strain in China) of MDV. Methods\ Two oligonucleotide primers were synthesized according to the reported sequence of \%meq\% gene an ideal oncogenic candidate and our previously determined sequence of BamHI L fragment of Marek′s disease herpesvirus (MDV), respectively. Reverse transcriptase PCR(RT PCR) assay was performed by using these primers and the mRNA as a template which was isolated from visceral lymphoblastoid tumors obtained from chickens artificially infected with strain Beijing 1 of oncogenic MDV. Southern blot molecular hybridization was further carried out to detect the product of RT PCR with digoxigenin labeled nucleotide probe from BamHI I2 and L fragment in the gene library of MDV strain GA, respectively. Results\ Two probes could simultaneously hybridize this cDNA amplified by RT PCR with a length of about 730 bp. Conclusion\ It is suggested that \%meq\% transcription could extend from the right hand end of BamHI I2 to the adjacent BamHI L, and the BamHI L region was likely to be transcribed in MDV induced lymphoblastoid tumors.展开更多
[ Objective] To prepare monoclonal antibodies against chicken immunoglobulin G （IgG） and improve the diagnostic level of specific antibodies in chickens. [ Method] Chicken IgG was isolated by saturated ammonium sulf...[ Objective] To prepare monoclonal antibodies against chicken immunoglobulin G （IgG） and improve the diagnostic level of specific antibodies in chickens. [ Method] Chicken IgG was isolated by saturated ammonium sulfate and purified by Sephadex G-200 column chromatography. Then the BALB/c mice were immunized by the chicken IgG, and the spleen cells were fused with mouse myeloma cells SP2/0. Finally, the positive hybridoma cells were screened and detected by indirect enzyme-linked immunosorbent assay （ELISA）. [ Result] Four hybridoma cell strains secre- ting monoclonal antibodies against chicken IgG were obtained and named as C44, C45, C67 and C68, and their ascites titers in indirect ELISA were 1 ： 640 000, 1 ： 320 000, 1 ： 640 000 and 1 ： 80 000, respectively. The monoclonal antibodies secreted by C44 and C45 could recognize light chains of chicken IgG and those secreted by C,67 and C68 could recognize heavy chains of chicken IgG. They all could not recognize IgG from duck, rabbit and swine. Additionally, the Ig type identification results showed that they all belonged to IgGl. [ Conclusion] Four cell strains of obtained hybridoma can stably produce the monoclonal antibodies against chicken IgG.展开更多
Electromagnetic Spectrum(EMS)recognition is vital in spectrum control,interference location,electronic countermeasures,etc.However,samples of high-value targets are incredibly scarce,even single,and are easily overwhe...Electromagnetic Spectrum(EMS)recognition is vital in spectrum control,interference location,electronic countermeasures,etc.However,samples of high-value targets are incredibly scarce,even single,and are easily overwhelmed by noise and numerous low-value targets,resulting in poor recognition accuracy using traditional methods.Furthermore,the great similarity between samples from the same manufacturer,model,and batch,makes Specific Emitter Identification(SEI)with the EMS especially challenging.Based on the powerful extension and extraction ability of the Fractional Fourier Transform(FrFT)for detailed features,this paper proposes a novel algorithm for the EMS recognition under a single-sample condition.The proposed method constructs a feature matrix FrFT-M from the results of the FrFT under specific orders for each sample.Then,the most relevant item,obtained by analyzing the correlations among FrFT-Ms between the unidentified sample and known samples,determines the optimal recognition.Three simple tests are conducted,including two simulations considering fifteen basic waveforms and six typical radar signals,and one experiment using STM32 microcontroller boards.The detection results of simulated and experimental data show that the accuracies of all three cases are higher than 86%,even for samples of the same model.Our method is promising and may have significant value in other fields.展开更多
Molecular diagnostics is one of the most important tools currently in use for clinical pathogen detection due to its high sensitivity,specificity,and low consume of sample and reagent is keyword to low cost molecular ...Molecular diagnostics is one of the most important tools currently in use for clinical pathogen detection due to its high sensitivity,specificity,and low consume of sample and reagent is keyword to low cost molecular diagnostics.In this paper,a sensitive DNA isothermal amplifi-cation method for fast clinical infectious diseases diagnostics at aM concentrations of DNA was developed using a polycarbonate(PC)microfuidic chip.A portable confocal optical fuo-rescence detector was specifically developed for the microfuidic chip that was capable of highly sensitive real-time detection of amplified products for sequence-specific molecular identification near the optical diffraction limit with low background.The molecular diagnostics of Listeria monocytogenes with nucleic acid extracted from stool samples was performed at a minimum DNA template concentration of 3.65 aM,and a detection limit of less than five copies of genomic DNA.Contrast to the general polymerase chain reaction(PCR)at eppendorf(EP)tube,the detection time in our developed method was reduced from 1.5h to 45 min for multi-target parallel detection,the consume of sample and reagent was dropped from 25μL to 1.45μL.This novel microfuidic chip system and method can be used to develop a micro total analysis system as a clinically relevant pathogen molecular diagnostics method via the amplification of targets,with potential applications in biotechnology,medicine,and clinical molecular diagnostics.展开更多
An unacceptable increase in antibacterial resistance has arisen due to the abuse of multiple classes of broad-spectrum antibiotics.Therefore,it is significant to develop new antibacterial agents,especially those that ...An unacceptable increase in antibacterial resistance has arisen due to the abuse of multiple classes of broad-spectrum antibiotics.Therefore,it is significant to develop new antibacterial agents,especially those that can accurately identify and kill specific bacteria.Herein,we demonstrate a kind of perilla-derived carbon nanodots(CNDs),integrating intrinsic advantages of luminescence and photodynamic,providing the opportunity to accurately identify and kill specific bacteria.The CNDs have an exotic-doped andπ-conjugated core,vitalizing them near-infrared(NIR)absorption and emission properties with photoluminescence quantum yield of 21.1%;hydrophobic chains onto the surface of the CNDs make them to selectively stain Gram-positive bacteria by insertion into their membranes.Due to the strong absorption in NIR region,reactive oxygen species are in situ generated by the CNDs onto bacterial membranes under 660 nm irradiation,and 99.99%inactivation efficiency against Gram-positive bacteria within 5 min can be achieved.In vivo results demonstrate that the CNDs with photodynamic antibacterial property can eliminate the inflammation of the area affected by methicillin-resistant Staphylococcus aureus(MRSA),and enabling the wound to be cured quickly.展开更多
基金supported by the National Natural Science Foundation of China(22078132,22108103,and U22A20413)the Open Funding Project of the National Key Labora-tory of Biochemical Engineering(2021KF-02)+3 种基金China Postdoctoral Science Foundation(2021M691301)Jiangsu Key Research and Development Program(BE2022356)the Postdoctoral Fellowship Program of China Postdoctoral Science Foundation(CPSF)(GZ20230989)Jiangsu Agricultural Independent Innovation Fund Project(CX(21)3079).
文摘Expanding the specific surface area of substrates and carrying out precise surface engineering of imprinted nanocavities are crucial methods for enhancing the identification efficiency of molecularly imprinted polymers(MIPs).To implement this synergistic strategy,bioinspired surface engineering was used to incorporate dual covalent receptors via precise post-imprinting modifications(PIMs)onto mesoporous silica nanosheets.The prepared sorbents(denoted as‘‘D-PMIPs”)were utilized to improve the specific identification of adenosine 5-monophosphate(AMP).Significantly,the mesoporous silica nanosheets possess a high surface area of approximately 498.73 m^(2)·g^(-1),which facilitates the formation of abundant specific recognition sites in the D-PMIPs.The dual covalent receptors are valuable for estab-lishing the spatial orientation and arrangement of AMP through multiple cooperative interactions.PIMs enable precise site-specific functionalization within the imprinted cavities,leading to the tailor-made formation of complementary binding sites.The maximum number of high-affinity binding sites(Nmax)of the D-PMIPs is 39.99 lmol·g^(-1),which is significantly higher than that of imprinted sorbents with a sin-gle receptor(i.e.,S-BMIPs or S-PMIPs).The kinetic data of the D-PMIPs can be effectively described by a pseudo-second-order model,indicating that the main binding mechanism involves synergistic chemisorption from boronate affinity and the pyrimidine base.This study suggests that using dual cova-lent receptors and PIMs is a reliable approach for creating imprinted sorbents with high selectivity,allow-ing for the controlled engineering of imprinted sites.
基金supported by the National Natural Science Foundation of China under Grant No.61671185 and 62071153.
文摘In the field of specific emitter identification(SEI),power amplifiers(PAs)have long been recognized as significant contributors to unintentional modulation characteristics.To enhance signal quality,digital pre-distortion(DPD)techniques are commonly employed in practical applications to mitigate the nonlinear effects of PAs.However,DPD techniques may diminish the distinctive characteristics of individual transmitters,potentially compromising SEI performance.This study investigates the influence of SEI in the presence of DPD applied to PAs.We construct a semi-physical emitter platform using AD9361 and ZYNQ,incorporating memory and non-memory models to emulate an amplification system comprising DPD devices and PAs.Furthermore,we delve into the analysis and evaluation of LMS-based and QRDRLS-based DPD algorithms to ascertain their efficacy in compensating for amplifier nonlinearity.Finally,we conduct a comprehensive set of experiments to demonstrate the adverse impact of DPD techniques on SEI.Our findings demonstrate a direct correlation between the degree of DPD performance and its impact magnitude on SEI,thereby providing a foundational basis for future studies investigating SEI techniques under DPD.
基金supported by the Youth Science and Technology Innovation Award of National University of Defense Technology (18/19-QNCXJ)the National Science Foundation of China (62271494)
文摘Extensive experiments suggest that kurtosis-based fingerprint features are effective for specific emitter identification (SEI). Nevertheless, the lack of mechanistic explanation restricts the use of fingerprint features to a data-driven technique and fur-ther reduces the adaptability of the technique to other datasets. To address this issue, the mechanism how the phase noise of high-frequency oscillators and the nonlinearity of power ampli-fiers affect the kurtosis of communication signals is investigated. Mathematical models are derived for intentional modulation (IM) and unintentional modulation (UIM). Analysis indicates that the phase noise of high-frequency oscillators and the nonlinearity of power amplifiers affect the kurtosis frequency and amplitude, respectively. A novel SEI method based on frequency and ampli-tude of the signal kurtosis (FA-SK) is further proposed. Simula-tion and real-world experiments validate theoretical analysis and also confirm the efficiency and effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China(62061003)Sichuan Science and Technology Program(2021YFG0192)the Research Foundation of the Civil Aviation Flight University of China(ZJ2020-04,J2020-033)。
文摘Existing specific emitter identification(SEI)methods based on hand-crafted features have drawbacks of losing feature information and involving multiple processing stages,which reduce the identification accuracy of emitters and complicate the procedures of identification.In this paper,we propose a deep SEI approach via multidimensional feature extraction for radio frequency fingerprints(RFFs),namely,RFFsNet-SEI.Particularly,we extract multidimensional physical RFFs from the received signal by virtue of variational mode decomposition(VMD)and Hilbert transform(HT).The physical RFFs and I-Q data are formed into the balanced-RFFs,which are then used to train RFFsNet-SEI.As introducing model-aided RFFs into neural network,the hybrid-driven scheme including physical features and I-Q data is constructed.It improves physical interpretability of RFFsNet-SEI.Meanwhile,since RFFsNet-SEI identifies individual of emitters from received raw data in end-to-end,it accelerates SEI implementation and simplifies procedures of identification.Moreover,as the temporal features and spectral features of the received signal are both extracted by RFFsNet-SEI,identification accuracy is improved.Finally,we compare RFFsNet-SEI with the counterparts in terms of identification accuracy,computational complexity,and prediction speed.Experimental results illustrate that the proposed method outperforms the counterparts on the basis of simulation dataset and real dataset collected in the anechoic chamber.
基金the National Natural Science Foundation of China(No.U20B2038,No.61871398,NO.61901520 and No.61931011)the Natural Science Foundation for Distinguished Young Scholars of Jiangsu Province(No.BK20190030)the National Key R&D Program of China under Grant 2018YFB1801103.
文摘Specific emitter identification can distin-guish individual transmitters by analyzing received signals and extracting inherent features of hard-ware circuits.Feature extraction is a key part of traditional machine learning-based methods,but manual extrac-tion is generally limited by prior professional knowl-edge.At the same time,it has been noted that the per-formance of most specific emitter identification meth-ods degrades in the low signal-to-noise ratio(SNR)environments.The deep residual shrinkage network(DRSN)is proposed for specific emitter identification,particularly in the low SNRs.The soft threshold can preserve more key features for the improvement of performance,and an identity shortcut can speed up the training process.We collect signals via the receiver to create a dataset in the actual environments.The DRSN is trained to automatically extract features and imple-ment the classification of transmitters.Experimental results show that DRSN obtains the best accuracy un-der different SNRs and has less running time,which demonstrates the effectiveness of DRSN in identify-ing specific emitters.
基金Supported by the National Natural Science Foundation of China under Grant No U1530126the Fundamental Research Funds for the Central Universities under Grant No ZYGX2015J022
文摘The specific emitter identification （SEI） technique some external feature measurements of the signal. determines the unique emitter of a given signal by using It has recently attracted a great deal of attention because many applications can benefit from it. This work addresses the SEI problem using two methods, namely, the normalized visibility graph entropy （NVGE） and the normalized horizontal visibility graph entropy （NHVGE） based on treating emitters as nonlinear dynamical systems. Firstly, the visibility graph （VG） and the horizontal visibility graph （HVG） are used to convert the instantaneous amplitude, phase and frequency of received signals into graphs. Then, based on the information captured by the VG and the HVG, the normalized Shannon entropy （NSE） calculated from the corresponding degree distributions are utilized as the rf fingerprint. Finally, four emitters from the same manufacturer are utilized to evaluate the performance of the two methods. Experimental results demonstrate that both the NHVGE-based method and NVGE-based method are quite effective and they perform much better than the method based on the normalized permutation entropy （NPE） in the case of a small amount of data. The NVGE-based method performs better than the NHVGE-based method since the VG can extract more information than the HVG does. Moreover, our methods do not distinguish between the transient signal and the steady-state signal, making it practical.
文摘Objective\ To understand the transcription of BamHI L DNA fragment from genome of strong virulent GA strain of Marek′s disease herpesvirus (MDV) in lymphoblastoid tumor tissue induced by oncogenic strain Beijing 1 (a specific local strain in China) of MDV. Methods\ Two oligonucleotide primers were synthesized according to the reported sequence of \%meq\% gene an ideal oncogenic candidate and our previously determined sequence of BamHI L fragment of Marek′s disease herpesvirus (MDV), respectively. Reverse transcriptase PCR(RT PCR) assay was performed by using these primers and the mRNA as a template which was isolated from visceral lymphoblastoid tumors obtained from chickens artificially infected with strain Beijing 1 of oncogenic MDV. Southern blot molecular hybridization was further carried out to detect the product of RT PCR with digoxigenin labeled nucleotide probe from BamHI I2 and L fragment in the gene library of MDV strain GA, respectively. Results\ Two probes could simultaneously hybridize this cDNA amplified by RT PCR with a length of about 730 bp. Conclusion\ It is suggested that \%meq\% transcription could extend from the right hand end of BamHI I2 to the adjacent BamHI L, and the BamHI L region was likely to be transcribed in MDV induced lymphoblastoid tumors.
基金supported by the National Natural Science Fund (30671537)
文摘[ Objective] To prepare monoclonal antibodies against chicken immunoglobulin G （IgG） and improve the diagnostic level of specific antibodies in chickens. [ Method] Chicken IgG was isolated by saturated ammonium sulfate and purified by Sephadex G-200 column chromatography. Then the BALB/c mice were immunized by the chicken IgG, and the spleen cells were fused with mouse myeloma cells SP2/0. Finally, the positive hybridoma cells were screened and detected by indirect enzyme-linked immunosorbent assay （ELISA）. [ Result] Four hybridoma cell strains secre- ting monoclonal antibodies against chicken IgG were obtained and named as C44, C45, C67 and C68, and their ascites titers in indirect ELISA were 1 ： 640 000, 1 ： 320 000, 1 ： 640 000 and 1 ： 80 000, respectively. The monoclonal antibodies secreted by C44 and C45 could recognize light chains of chicken IgG and those secreted by C,67 and C68 could recognize heavy chains of chicken IgG. They all could not recognize IgG from duck, rabbit and swine. Additionally, the Ig type identification results showed that they all belonged to IgGl. [ Conclusion] Four cell strains of obtained hybridoma can stably produce the monoclonal antibodies against chicken IgG.
基金supported in part by the National Natural Science Foundation of China(No.62293495)。
文摘Electromagnetic Spectrum(EMS)recognition is vital in spectrum control,interference location,electronic countermeasures,etc.However,samples of high-value targets are incredibly scarce,even single,and are easily overwhelmed by noise and numerous low-value targets,resulting in poor recognition accuracy using traditional methods.Furthermore,the great similarity between samples from the same manufacturer,model,and batch,makes Specific Emitter Identification(SEI)with the EMS especially challenging.Based on the powerful extension and extraction ability of the Fractional Fourier Transform(FrFT)for detailed features,this paper proposes a novel algorithm for the EMS recognition under a single-sample condition.The proposed method constructs a feature matrix FrFT-M from the results of the FrFT under specific orders for each sample.Then,the most relevant item,obtained by analyzing the correlations among FrFT-Ms between the unidentified sample and known samples,determines the optimal recognition.Three simple tests are conducted,including two simulations considering fifteen basic waveforms and six typical radar signals,and one experiment using STM32 microcontroller boards.The detection results of simulated and experimental data show that the accuracies of all three cases are higher than 86%,even for samples of the same model.Our method is promising and may have significant value in other fields.
基金the National Natural Science Foundation of China(81327005,61361160418,61575100)the National Foundation of High Technology of China(2012 AA020102,2013 AA041201)+2 种基金the National Key Foundation for Exploring Scientific Instruments(2013 YQ190467)the Beijing Municipal Natural Science Foundation(4142025)the Beijing Lab Foundation,and the Tsinghua Autonomous Research Foundation(2014 Z01001)。
文摘Molecular diagnostics is one of the most important tools currently in use for clinical pathogen detection due to its high sensitivity,specificity,and low consume of sample and reagent is keyword to low cost molecular diagnostics.In this paper,a sensitive DNA isothermal amplifi-cation method for fast clinical infectious diseases diagnostics at aM concentrations of DNA was developed using a polycarbonate(PC)microfuidic chip.A portable confocal optical fuo-rescence detector was specifically developed for the microfuidic chip that was capable of highly sensitive real-time detection of amplified products for sequence-specific molecular identification near the optical diffraction limit with low background.The molecular diagnostics of Listeria monocytogenes with nucleic acid extracted from stool samples was performed at a minimum DNA template concentration of 3.65 aM,and a detection limit of less than five copies of genomic DNA.Contrast to the general polymerase chain reaction(PCR)at eppendorf(EP)tube,the detection time in our developed method was reduced from 1.5h to 45 min for multi-target parallel detection,the consume of sample and reagent was dropped from 25μL to 1.45μL.This novel microfuidic chip system and method can be used to develop a micro total analysis system as a clinically relevant pathogen molecular diagnostics method via the amplification of targets,with potential applications in biotechnology,medicine,and clinical molecular diagnostics.
基金the National Natural Science Foundation of China(Nos.11904326,62075198,U2004168 and 12074348)China Postdoctoral Science Foundation(Nos.2019TQ0287 and 2019M662510).
文摘An unacceptable increase in antibacterial resistance has arisen due to the abuse of multiple classes of broad-spectrum antibiotics.Therefore,it is significant to develop new antibacterial agents,especially those that can accurately identify and kill specific bacteria.Herein,we demonstrate a kind of perilla-derived carbon nanodots(CNDs),integrating intrinsic advantages of luminescence and photodynamic,providing the opportunity to accurately identify and kill specific bacteria.The CNDs have an exotic-doped andπ-conjugated core,vitalizing them near-infrared(NIR)absorption and emission properties with photoluminescence quantum yield of 21.1%;hydrophobic chains onto the surface of the CNDs make them to selectively stain Gram-positive bacteria by insertion into their membranes.Due to the strong absorption in NIR region,reactive oxygen species are in situ generated by the CNDs onto bacterial membranes under 660 nm irradiation,and 99.99%inactivation efficiency against Gram-positive bacteria within 5 min can be achieved.In vivo results demonstrate that the CNDs with photodynamic antibacterial property can eliminate the inflammation of the area affected by methicillin-resistant Staphylococcus aureus(MRSA),and enabling the wound to be cured quickly.
