Lemon oils are broadly used as flavoring agents in beverages,foods,cosmetics and pharmaceuticals,yet the adulteration of natural,particularly cold pressed lemon oils is very common in the industry due to its unmet dem...Lemon oils are broadly used as flavoring agents in beverages,foods,cosmetics and pharmaceuticals,yet the adulteration of natural,particularly cold pressed lemon oils is very common in the industry due to its unmet demand and high cost.Nowadays,most quality control(QC)analysis of lemon oils is conducted by gas chromatography(GC)analysis,which is far from a reliable method.Oxygen heterocyclic compounds(OHCs)in non-volatile fraction are gaining increasing attention in authentication process because of the nearly finger-printing profiles of OHCs in cold pressed citrus essential oils.Our goal in this study was to identify OHCs using high performance liquid chromatography(HPLC)in lemon oils,establish OHC profiles,perform stepwise logistic regression analysis(SLRA)and build effective predicting model and further determine adulterated lemon oils by referencing the OHC profiles and established models.After HPLC analyses,profiling and SLRA modeling of 154 OHCs samples of industrial lemon oils,we found that the combination of isopimpinellin and total OHC concentration are essential and robust predictors to differentiate authentic samples from adulterated lemon oils with a success rate of 98%from the 5-fold cross validation.This study provided a reliable and efficient method in determining the authenticity of lemon oils.展开更多
Over 11% of all pregnancies in the US result in preterm birth, greatly contributing to perinatal morbidity and mortality （Goldenberg and Rouse, 1998）. Preterm birth etiologies remain largely unknown, and effective p...Over 11% of all pregnancies in the US result in preterm birth, greatly contributing to perinatal morbidity and mortality （Goldenberg and Rouse, 1998）. Preterm birth etiologies remain largely unknown, and effective prevention methods have yet to be developed. The use of biofluid （e.g., serum or urine） for the analysis of the naturally occurring peptidome （MW 〈 4000） as a source of biomarkers has been reported for different diseases （Villanueva et al., 2006; Ling et al., 2010a, 2010b, 2010c, 2011）. Mass spectrometry-based profiling of naturally occurring peptides can provide an extensive in- ventory of serum peptides derived from either high-abundant endogenous circulating proteins or cell and tissue proteins （Liotta and Petricoin, 2006）.展开更多
Dualcolor systems were used to reduce the collinearity of multicomponent spectra, which is described by the angles between spectra vectors. Combined with iterative target transformation factor analysis, single rare ea...Dualcolor systems were used to reduce the collinearity of multicomponent spectra, which is described by the angles between spectra vectors. Combined with iterative target transformation factor analysis, single rare earth element was determined in its mixture. The calculated results show that the average angle between rare earth spectra in one color system(trichloroarsenazorare earths, pH 34) is 45, and that in two color systems(trichloroarsenazorare earths, pH 34, 14) is 215. This technique makes it easy to select the real number of the components in mixtures, and the determination results show dualcolor system method is an effective technique in rare earth mixture analysis.展开更多
Embryonic stem (ES) cells are under precise control of both intrinsic self-renewal gene regulatory network and extrinsic growth factor-triggered signaling cascades.
Cyanotoxins produced by cyanobacteria are formidable threats to aquatic ecosystems and public health worldwide. The potential health risks associated with cyanotoxins from contaminated fishponds are becoming a growing...Cyanotoxins produced by cyanobacteria are formidable threats to aquatic ecosystems and public health worldwide. The potential health risks associated with cyanotoxins from contaminated fishponds are becoming a growing concern, as cyanotoxin production has steadily increased over time in these aquatic environments. Therefore, this study aims to utilize targeted and non-targeted Liquid Chromatography Mass Spectrometer (LC-MS) analytical methods to detect cyanotoxins in catfish (Clarias gariepinus) tissue harvested from fishponds. For detecting cyanotoxins in fish tissue utilizing the non-targeted approach, high-resolution MS/MS spectra data obtained from the analysis were converted to mzML format, analyzed with the Global Natural Product Social (GNPS) Library and CANOPUS annotations for LEVEL 3 metabolite identification, and visualized as a molecular network in Cytoscape. Regarding the targeted method, the toxin identification and quantification were achieved by comparing samples spiked with known concentrations of MC-RR and YR to an authentic toxin standard. The results of the target analysis showed that microcystin variant MC-RR was not detected in the fish tissue. The MC-YR variant was detected in the intestines and gills of Clarias gariepinus at concentrations of 13.2–10.6 μg/g and 1.5–13.9 μg/g, respectively. The muscle tissues across all fish ponds showed MC-YR concentrations between 10.5 and 16.06 μg/g. The highest concentration of MC-YR was found in the liver tissue in pond 6 (20.9 μg/g). The untargeted LC-MS method led to the identification of a larger number of cyanometabolites in the fish tissue, such as aeruginosins, anabaenopeptins, microginins. Non-toxic secondary metabolites like octadecadienoic acid, while phosphocholine (PC), ethanesulfonic acid, pheophorbide A, microcolins, cholic acid, phenylalanine, amyl amine and phosphocholine (PC), triglyceride (TG), phosphocholine (PC) and sulfonic acid derieved from cyanobacteria, fish and anthropogenic sources were also detected in the fish tissues. The non-targeted analysis facilitates the identification of both unexpected and unknown compounds.展开更多
This paper proposes a PCA and KPCA self-fusion based MSTAR SAR automatic target recognition algorithm. This algorithm combines the linear feature extracted from principal component analysis （PCA） and nonlinear featu...This paper proposes a PCA and KPCA self-fusion based MSTAR SAR automatic target recognition algorithm. This algorithm combines the linear feature extracted from principal component analysis （PCA） and nonlinear feature extracted from kernel principal component analysis （KPCA） respectively, and then utilizes the adaptive feature fusion algorithm which is based on the weighted maximum margin criterion （WMMC） to fuse the features in order to achieve better performance. The linear regression classifier is used in the experiments. The experimental results indicate that the proposed self-fusion algorithm achieves higher recognition rate compared with the traditional PCA and KPCA feature fusion algorithms.展开更多
Targeted multimodal sentiment classification(TMSC)aims to identify the sentiment polarity of a target mentioned in a multimodal post.The majority of current studies on this task focus on mapping the image and the text...Targeted multimodal sentiment classification(TMSC)aims to identify the sentiment polarity of a target mentioned in a multimodal post.The majority of current studies on this task focus on mapping the image and the text to a high-dimensional space in order to obtain and fuse implicit representations,ignoring the rich semantic information contained in the images and not taking into account the contribution of the visual modality in the multimodal fusion representation,which can potentially influence the results of TMSC tasks.This paper proposes a general model for Improving Targeted Multimodal Sentiment Classification with Semantic Description of Images(ITMSC)as a way to tackle these issues and improve the accu-racy of multimodal sentiment analysis.Specifically,the ITMSC model can automatically adjust the contribution of images in the fusion representation through the exploitation of semantic descriptions of images and text similarity relations.Further,we propose a target-based attention module to capture the target-text relevance,an image-based attention module to capture the image-text relevance,and a target-image matching module based on the former two modules to properly align the target with the image so that fine-grained semantic information can be extracted.Our experimental results demonstrate that our model achieves comparable performance with several state-of-the-art approaches on two multimodal sentiment datasets.Our findings indicate that incorporating semantic descriptions of images can enhance our understanding of multimodal content and lead to improved sentiment analysis performance.展开更多
Vision-based target motion estimation based Kalman filtering or least-squares estimators is an important problem in many tasks such as vision-based swarming or vision-based target pursuit.In this paper,we focus on a p...Vision-based target motion estimation based Kalman filtering or least-squares estimators is an important problem in many tasks such as vision-based swarming or vision-based target pursuit.In this paper,we focus on a problem that is very specific yet we believe important.That is,from the vision measurements,we can formulate various measurements.Which and how the measurements should be used?These problems are very fundamental,but we notice that practitioners usually do not pay special attention to them and often make mistakes.Motivated by this,we formulate three pseudo-linear measurements based on the bearing and angle measurements,which are standard vision measurements that can be obtained.Different estimators based on Kalman filtering and least-squares estimation are established and compared based on numerical experiments.It is revealed that correctly analyzing the covariance noises is critical for the Kalman filtering-based estimators.When the variance of the original measurement noise is unknown,the pseudo-linear least-squares estimator that has the smallest magnitude of the transformed noise can be a good choice.展开更多
The target motion analysis（TMA） for a moving scanning emitter with known fixed scan rate by a single observer using the time of interception（TOI） measurements only is investigated in this paper.By transforming the...The target motion analysis（TMA） for a moving scanning emitter with known fixed scan rate by a single observer using the time of interception（TOI） measurements only is investigated in this paper.By transforming the TOI of multiple scan cycles into the direction difference of arrival（DDOA） model,the observability analysis for the TMA problem is performed.Some necessary conditions for uniquely identifying the scanning emitter trajectory are obtained.This paper also proposes a weighted instrumental variable（WIV） estimator for the scanning emitter TMA,which does not require any initial solution guess and is closed-form and computationally attractive.More importantly,simulations show that the proposed algorithm can provide estimation mean square error close to the Cramer-Rao lower bound（CRLB） at moderate noise levels with significantly lower estimation bias than the conventional pseudo-linear least square（PLS） estimator.展开更多
Objective: To investigate the current status of health literacy regarding children’s vision protection among preschool teachers and to provide a basis for targeted training. Methods: A convenience sampling method was...Objective: To investigate the current status of health literacy regarding children’s vision protection among preschool teachers and to provide a basis for targeted training. Methods: A convenience sampling method was employed to conduct a questionnaire survey among 1,442 preschool teachers in Xiangyang City from April to June 2024. The questionnaire covered five dimensions: knowledge, beliefs, behaviors, skills, and policies. Item response rates were used to identify literacy gaps. Results: The overall vision protection literacy of preschool teachers exhibited characteristics of “strong beliefs but weak knowledge and skills”. The item response rates for each dimension, from highest to lowest, were: beliefs (92.7%), policies (81.9%), behaviors (74.8%), knowledge (67.5%), and skills (58.3%). The core gaps were concentrated in the “knowledge” and “skills” dimensions, with significant deficiencies particularly in the understanding of the concept of “hyperopia reserve” (awareness rate: 27.6%), skills in guiding behaviors for myopia prevention and control (mastery rate: < 50%), and the ability to interpret vision screening results (complete mastery rate: 35.0%). Conclusion: Currently, there are significant structural deficiencies in the health literacy of kindergarten teachers regarding children’s vision protection. In the future, greater emphasis should be placed on practical skills training, particularly in enhancing their practical abilities in areas such as “hyperopia reserve” cognition and interpretation of vision screening results.展开更多
Cancer,like other diseases accompanied by metabolic changes,shows characteristic DNA/RNA modifications and activities of modifying enzymes,resulting in fluctuations in nucleoside levels.In this study,we undertook targ...Cancer,like other diseases accompanied by metabolic changes,shows characteristic DNA/RNA modifications and activities of modifying enzymes,resulting in fluctuations in nucleoside levels.In this study,we undertook targeted metabolomic analyses of nucleotides in different cancer cell culture models using a sensitive and reproducible ion-pair HPLC method.The experimental data were analyzed by principal component analysis(PCA)to identify potential biomarkers in cancer cells,and statistical significance was determined by one-way analysis of variance.As a result,a clear differentiation of normal and tumor cells into two clusters was shown,indicating abnormal metabolism of nucleotides in tumor cells.Six variables(AMP,UDP,CTP levels with a significance of Po0.05;ATP,UTP and GMP levels with a significance of Po0.01)were considered as potential biomarkers;the content of AMP,UTP,GMP and ATP was significantly higher in cancer cells.The receiver operating characteristic(ROC)curve analysis allowed us to discriminate normal cells from tumor cells based on area under the curve(AUC).The sequence of their AUC values were:ATP(0.979)4UTP(0.938)4CTP¼GMP(0.896)4AMP(0.812)4UDP(0.792),so we conclude that ATP and UTP are the best potential biomarkers in tumor cells.This study may provide a valuable tool for studying minute alterations of intracellular nucleotide pools induced by anticancer/antiviral drugs,diseases or environmental factors.展开更多
Objective： We aimed to evaluate the clinicopathologic characteristics, immunohistochemical expression and prognostic factors of patients with primary gastrointestinal stromal tumors（GISTs）.Methods： Data from 2,570...Objective： We aimed to evaluate the clinicopathologic characteristics, immunohistochemical expression and prognostic factors of patients with primary gastrointestinal stromal tumors（GISTs）.Methods： Data from 2,570 consecutive GIST patients from four medical centers in China（January2001–December 2015） were reviewed. Survival curves were constructed by the Kaplan-Meier method, and Cox regression models were used to identify independent prognostic factors.Results： Of the included patients, 1,375（53.5%） were male, and the patient age range was 18 to 95（median, 58）years. The tumors were mostly found in the stomach（64.5%）, small intestine（25.1%） and colorectal region（5.1%）.At the time of diagnosis, the median tumor size was 4.0（range： 0.1–55.0） cm, and the median mitotic index per 50 high power fields（HPFs） was 3（range： 0–254）. Of the 2,168 resected patients, 2,009（92.7%） received curative resection. According to the modified National Institutes of Health（NIH） classification, 21.9%, 28.9%, 14.1% and35.1% were very low-, low-, intermediate-and high-risk tumors, respectively. The rate of positivity was 96.4% for c-Kit, 87.1% for CD34, 96.9% for delay of germination 1（DOG-1）, 8.0% for S-100, 31.0% for smooth muscle actin（SMA） and 5.1% for desmin. However, the prognostic value of each was limited. Multivariate analysis showed that age, tumor size, mitotic index, tumor site, occurrence of curative resection and postoperative imatinib were independent prognostic factors. Furthermore, we found that high-risk patients benefited significantly from postoperative imatinib（P〈0.001）, whereas intermediate-risk patients did not（P=0.954）.Conclusions： Age, tumor size, mitotic index, tumor site, occurrence of curative resection and postoperative imatinib were independent prognostic factors in patients with GISTs. Moreover, determining whether intermediate-risk patients can benefit from adjuvant imatinib would be of considerable interest in future studies.展开更多
There exist a large class of acoustic sources which have an underlying periodic phenomenon. Unlike the well-studied Bearings-Only Tracking(BOT) of an aperiodic acoustic source,this paper considers the problem of track...There exist a large class of acoustic sources which have an underlying periodic phenomenon. Unlike the well-studied Bearings-Only Tracking(BOT) of an aperiodic acoustic source,this paper considers the problem of tracking a periodic acoustic source. For periodic acoustic tracking, the signal emission time is known. However, the true measurement reception time is unknown because it is corrupted by noise due to propagation delay. We augment the sensor’s signal reception time onto bearing measurements, and the information of the delay constraint is included in the original bearing measurements to compensate for the propagation delay. A Cubature Kalman Filter(CKF) is used for periodic acoustic source tracking, in which measurement prediction cannot be obtained directly because the sensor’s position at the true measurement reception time is unknown.We solve this problem by using the implicit Gauss-Helmert Sensor Model(GHSM) for estimating the sensor’s position, which consists of the sensor’s motion equation and the known measured sensor’s signal reception time equation related to the state. Then a CKF based on the GHSM(CF-GHSM) is developed for periodic acoustic tracking. Illustrative examples demonstrate that the CF-GHSM algorithm is better than other algorithms for periodic acoustic source tracking.展开更多
The problem of estimation of underwater target motion parameters via bearings only is the most of ten encountered and most difficult to solve in the underwater target motion analysis.As the bearings-only target motion...The problem of estimation of underwater target motion parameters via bearings only is the most of ten encountered and most difficult to solve in the underwater target motion analysis.As the bearings-only target motion analysis is a nonlinear and multiextremal global optimization problem, so most classical estimation methods often lead the solution to convergence to one of the local extremes other than the global extreme, especially, when the noise of target bearing observation is added. In this paper we propose to use the Generalized Least Square method on the rough estimation of target motion parameters, and then use the Sequential Uniform Design method to gain a more precise estimation on the bases of rough estimation.The latter ensures that the result convergences to the global extreme. The algorithm based on the above two methods is profitable for the bearings-only target motion analysis even under conditions of large bearing observation error.展开更多
The method for Bearings-Only Target Motion Analysis (BO-TMA) based on bearing measurements fusion of two arrays is studied. The algorithms of pseudolinear processing, extended Kalman filter and maximum likelihood est...The method for Bearings-Only Target Motion Analysis (BO-TMA) based on bearing measurements fusion of two arrays is studied. The algorithms of pseudolinear processing, extended Kalman filter and maximum likelihood estimation are presented. The results of simulation experiments show that the BO-TMA method based on association of multiple arrays not only makes contributions towards eliminating maneuvers needed by bearings-only TMA based on single array,but also improves the stabilization and global convergence for varied estimation algorithms.展开更多
Local-linear-prediction in phase space is performed for the underwater acoustic target radiated noise. Relation curve of average prediction error versus neighboring points' number is calculated. The result is used...Local-linear-prediction in phase space is performed for the underwater acoustic target radiated noise. Relation curve of average prediction error versus neighboring points' number is calculated. The result is used in judging the nonlinearity of radiated noise time series, and obtaining the appropriate form and coefficients of predicting model. The line and continuous spectral component are predicted respectively. Choice of some model parameters minimizing the prediction error is also discussed.展开更多
The normalized central moments are widely used in pattern recognition because of scale and translation invariance. The moduli of normalized central moments of the 1-dimensional complex range profiles are used here as ...The normalized central moments are widely used in pattern recognition because of scale and translation invariance. The moduli of normalized central moments of the 1-dimensional complex range profiles are used here as feature vector for radar target recognition. The common feature extraction method for high resolution range profile obtained by using Fourier-modified direct Mellin transform is inefficient and unsatisfactory in recognition rate And. generally speaking, the automatic target recognition method based on inverse synthetic aperture radar 2-dimensional imaging is not competent for real time object identification task because it needs complicated motion compensation which is sometimes too difficult to carry out. While the method applied here is competent for real-time recognition because of its computational efficiency. The result of processing experimental data indicates that this method is good at recognition.展开更多
We propose and demonstrate a scheme to smooth and shape the on-target patterns in multimode fiber lasers, which includes expanding-collimating system and lens array （LA）. A smooth pattern with flat-top and sharp-edg...We propose and demonstrate a scheme to smooth and shape the on-target patterns in multimode fiber lasers, which includes expanding-collimating system and lens array （LA）. A smooth pattern with flat-top and sharp-edge profiles can be obtained with the irradiation nonuniformity decreasing significantly. We analyze the effects of the parameters such as defocus distance, the tilt angles, the number of the incident fiber lasers, and the diffraction-weakened LA on the uniformity irradiation of target by numerical simulations.展开更多
In the traditional research of volatile compounds, some trace-level compounds could not be identified by gas chromatography-mass spectrometry. Target and post-targeted methods were applied in the investigation of trac...In the traditional research of volatile compounds, some trace-level compounds could not be identified by gas chromatography-mass spectrometry. Target and post-targeted methods were applied in the investigation of trace-level volatile compounds in fresh turf crop （Lolium perenne L.） based on gas chromatography in combination with hybrid quadrupole time-of-flight mass spectrometry. According to literatures published, a target analysis was performed by using retention index, accurate masses of characteristic ions and second-stage mass spectra （MS2 spectra）. And a series of experiments showed that low electron impact energy was beneficial to the improvement of the abundances of low abundance molecular ion peak. peak was beneficial to qualitative analysis. Totally, 60 Enhancing the abundances of low abundance molecular ion volatile compounds were identified, the great majority cornpounds of which were benzeneacetaldehyde （14.8%）, 2,5-dimethyl-pyrazine （9.6%）, and hexanal （9.3%）. Identification was complied by mass spectral search, retention index and accurate masses of characteristic ions.展开更多
After decades of development,protein and peptide drugs have now grown into a major drug class in the marketplace.Target identification and validation are crucial for the discovery of protein and peptide drugs,and bioi...After decades of development,protein and peptide drugs have now grown into a major drug class in the marketplace.Target identification and validation are crucial for the discovery of protein and peptide drugs,and bioinformatics prediction of targets based on the characteristics of known target proteins will help improve the efficiency and success rate of target selection.However,owing to the developmental history in the pharmaceutical industry,previous systematic exploration of the target spaces has mainly focused on traditional small-molecule drugs,while studies related to protein and peptide drugs are lacking.Here,we systematically explore the target spaces in the human genome specifically for protein and peptide drugs.Compared with other proteins,both successful protein and peptide drug targets have many special characteristics,and are also significantly different from those of small-molecule drugs in many aspects.Based on these features,we develop separate effective genome-wide target prediction models for protein and peptide drugs.Finally,a user-friendly web server,Predictor Of Protein and Pept Ide drugs’therapeutic Targets(POPPIT)(http://poppit.ncpsb.org.cn/),is established,which provides not only target prediction specifically for protein and peptide drugs but also abundant annotations for predicted targets.展开更多
文摘Lemon oils are broadly used as flavoring agents in beverages,foods,cosmetics and pharmaceuticals,yet the adulteration of natural,particularly cold pressed lemon oils is very common in the industry due to its unmet demand and high cost.Nowadays,most quality control(QC)analysis of lemon oils is conducted by gas chromatography(GC)analysis,which is far from a reliable method.Oxygen heterocyclic compounds(OHCs)in non-volatile fraction are gaining increasing attention in authentication process because of the nearly finger-printing profiles of OHCs in cold pressed citrus essential oils.Our goal in this study was to identify OHCs using high performance liquid chromatography(HPLC)in lemon oils,establish OHC profiles,perform stepwise logistic regression analysis(SLRA)and build effective predicting model and further determine adulterated lemon oils by referencing the OHC profiles and established models.After HPLC analyses,profiling and SLRA modeling of 154 OHCs samples of industrial lemon oils,we found that the combination of isopimpinellin and total OHC concentration are essential and robust predictors to differentiate authentic samples from adulterated lemon oils with a success rate of 98%from the 5-fold cross validation.This study provided a reliable and efficient method in determining the authenticity of lemon oils.
基金supported by the March of Dimes Prematurity Research Center at Stanford University, the Stanford Child Health Research Institutethe Stanford Clinical and Translational Science Award (CTSA) to Spectrum (UL1 TR001085)+1 种基金The CTSA program is led by the National Center for Advancing Translational Sciences (NCATS) at the National Institutes of Health (NIH)supported in part by the National Natural Science Foundation of China (NSFC) to ZT (No. 31201697)
文摘Over 11% of all pregnancies in the US result in preterm birth, greatly contributing to perinatal morbidity and mortality （Goldenberg and Rouse, 1998）. Preterm birth etiologies remain largely unknown, and effective prevention methods have yet to be developed. The use of biofluid （e.g., serum or urine） for the analysis of the naturally occurring peptidome （MW 〈 4000） as a source of biomarkers has been reported for different diseases （Villanueva et al., 2006; Ling et al., 2010a, 2010b, 2010c, 2011）. Mass spectrometry-based profiling of naturally occurring peptides can provide an extensive in- ventory of serum peptides derived from either high-abundant endogenous circulating proteins or cell and tissue proteins （Liotta and Petricoin, 2006）.
文摘Dualcolor systems were used to reduce the collinearity of multicomponent spectra, which is described by the angles between spectra vectors. Combined with iterative target transformation factor analysis, single rare earth element was determined in its mixture. The calculated results show that the average angle between rare earth spectra in one color system(trichloroarsenazorare earths, pH 34) is 45, and that in two color systems(trichloroarsenazorare earths, pH 34, 14) is 215. This technique makes it easy to select the real number of the components in mixtures, and the determination results show dualcolor system method is an effective technique in rare earth mixture analysis.
文摘Embryonic stem (ES) cells are under precise control of both intrinsic self-renewal gene regulatory network and extrinsic growth factor-triggered signaling cascades.
基金the National Research Foundation under grant number[SFH150715126382],in addition,to support from the Association of African Universities and the Research Publication Committee(RPC)at the University of Venda.
文摘Cyanotoxins produced by cyanobacteria are formidable threats to aquatic ecosystems and public health worldwide. The potential health risks associated with cyanotoxins from contaminated fishponds are becoming a growing concern, as cyanotoxin production has steadily increased over time in these aquatic environments. Therefore, this study aims to utilize targeted and non-targeted Liquid Chromatography Mass Spectrometer (LC-MS) analytical methods to detect cyanotoxins in catfish (Clarias gariepinus) tissue harvested from fishponds. For detecting cyanotoxins in fish tissue utilizing the non-targeted approach, high-resolution MS/MS spectra data obtained from the analysis were converted to mzML format, analyzed with the Global Natural Product Social (GNPS) Library and CANOPUS annotations for LEVEL 3 metabolite identification, and visualized as a molecular network in Cytoscape. Regarding the targeted method, the toxin identification and quantification were achieved by comparing samples spiked with known concentrations of MC-RR and YR to an authentic toxin standard. The results of the target analysis showed that microcystin variant MC-RR was not detected in the fish tissue. The MC-YR variant was detected in the intestines and gills of Clarias gariepinus at concentrations of 13.2–10.6 μg/g and 1.5–13.9 μg/g, respectively. The muscle tissues across all fish ponds showed MC-YR concentrations between 10.5 and 16.06 μg/g. The highest concentration of MC-YR was found in the liver tissue in pond 6 (20.9 μg/g). The untargeted LC-MS method led to the identification of a larger number of cyanometabolites in the fish tissue, such as aeruginosins, anabaenopeptins, microginins. Non-toxic secondary metabolites like octadecadienoic acid, while phosphocholine (PC), ethanesulfonic acid, pheophorbide A, microcolins, cholic acid, phenylalanine, amyl amine and phosphocholine (PC), triglyceride (TG), phosphocholine (PC) and sulfonic acid derieved from cyanobacteria, fish and anthropogenic sources were also detected in the fish tissues. The non-targeted analysis facilitates the identification of both unexpected and unknown compounds.
基金supported in part by the National Natural Science Foundation of China under Grant No. 61033012, No. 611003177, and No. 61070181Fundamental Research Funds for the Central Universities under Grant No.1600-852016 and No. DUT12JR07
文摘This paper proposes a PCA and KPCA self-fusion based MSTAR SAR automatic target recognition algorithm. This algorithm combines the linear feature extracted from principal component analysis （PCA） and nonlinear feature extracted from kernel principal component analysis （KPCA） respectively, and then utilizes the adaptive feature fusion algorithm which is based on the weighted maximum margin criterion （WMMC） to fuse the features in order to achieve better performance. The linear regression classifier is used in the experiments. The experimental results indicate that the proposed self-fusion algorithm achieves higher recognition rate compared with the traditional PCA and KPCA feature fusion algorithms.
文摘Targeted multimodal sentiment classification(TMSC)aims to identify the sentiment polarity of a target mentioned in a multimodal post.The majority of current studies on this task focus on mapping the image and the text to a high-dimensional space in order to obtain and fuse implicit representations,ignoring the rich semantic information contained in the images and not taking into account the contribution of the visual modality in the multimodal fusion representation,which can potentially influence the results of TMSC tasks.This paper proposes a general model for Improving Targeted Multimodal Sentiment Classification with Semantic Description of Images(ITMSC)as a way to tackle these issues and improve the accu-racy of multimodal sentiment analysis.Specifically,the ITMSC model can automatically adjust the contribution of images in the fusion representation through the exploitation of semantic descriptions of images and text similarity relations.Further,we propose a target-based attention module to capture the target-text relevance,an image-based attention module to capture the image-text relevance,and a target-image matching module based on the former two modules to properly align the target with the image so that fine-grained semantic information can be extracted.Our experimental results demonstrate that our model achieves comparable performance with several state-of-the-art approaches on two multimodal sentiment datasets.Our findings indicate that incorporating semantic descriptions of images can enhance our understanding of multimodal content and lead to improved sentiment analysis performance.
文摘Vision-based target motion estimation based Kalman filtering or least-squares estimators is an important problem in many tasks such as vision-based swarming or vision-based target pursuit.In this paper,we focus on a problem that is very specific yet we believe important.That is,from the vision measurements,we can formulate various measurements.Which and how the measurements should be used?These problems are very fundamental,but we notice that practitioners usually do not pay special attention to them and often make mistakes.Motivated by this,we formulate three pseudo-linear measurements based on the bearing and angle measurements,which are standard vision measurements that can be obtained.Different estimators based on Kalman filtering and least-squares estimation are established and compared based on numerical experiments.It is revealed that correctly analyzing the covariance noises is critical for the Kalman filtering-based estimators.When the variance of the original measurement noise is unknown,the pseudo-linear least-squares estimator that has the smallest magnitude of the transformed noise can be a good choice.
基金co-supported by the Shanghai Aerospace Science and Technology Innovation Fund of China(No.SAST2015028)the Equipment Prophecy Fund of China(No.9140A21040115KG01001)
文摘The target motion analysis（TMA） for a moving scanning emitter with known fixed scan rate by a single observer using the time of interception（TOI） measurements only is investigated in this paper.By transforming the TOI of multiple scan cycles into the direction difference of arrival（DDOA） model,the observability analysis for the TMA problem is performed.Some necessary conditions for uniquely identifying the scanning emitter trajectory are obtained.This paper also proposes a weighted instrumental variable（WIV） estimator for the scanning emitter TMA,which does not require any initial solution guess and is closed-form and computationally attractive.More importantly,simulations show that the proposed algorithm can provide estimation mean square error close to the Cramer-Rao lower bound（CRLB） at moderate noise levels with significantly lower estimation bias than the conventional pseudo-linear least square（PLS） estimator.
基金Nursing Discipline Research Project of the Chinese Medical Association Journal House for 2022-2023(Project No.:CMAPH-NRG 2022007)。
文摘Objective: To investigate the current status of health literacy regarding children’s vision protection among preschool teachers and to provide a basis for targeted training. Methods: A convenience sampling method was employed to conduct a questionnaire survey among 1,442 preschool teachers in Xiangyang City from April to June 2024. The questionnaire covered five dimensions: knowledge, beliefs, behaviors, skills, and policies. Item response rates were used to identify literacy gaps. Results: The overall vision protection literacy of preschool teachers exhibited characteristics of “strong beliefs but weak knowledge and skills”. The item response rates for each dimension, from highest to lowest, were: beliefs (92.7%), policies (81.9%), behaviors (74.8%), knowledge (67.5%), and skills (58.3%). The core gaps were concentrated in the “knowledge” and “skills” dimensions, with significant deficiencies particularly in the understanding of the concept of “hyperopia reserve” (awareness rate: 27.6%), skills in guiding behaviors for myopia prevention and control (mastery rate: < 50%), and the ability to interpret vision screening results (complete mastery rate: 35.0%). Conclusion: Currently, there are significant structural deficiencies in the health literacy of kindergarten teachers regarding children’s vision protection. In the future, greater emphasis should be placed on practical skills training, particularly in enhancing their practical abilities in areas such as “hyperopia reserve” cognition and interpretation of vision screening results.
基金support of Natural Science Foundation of Liaoning Province(No.201102210)Program for Liaoning Innovative Research Team in University(No.LH2012018)National Undergraduate Training Programs for Innovation and Entrepreneurship(No.201210163007).
文摘Cancer,like other diseases accompanied by metabolic changes,shows characteristic DNA/RNA modifications and activities of modifying enzymes,resulting in fluctuations in nucleoside levels.In this study,we undertook targeted metabolomic analyses of nucleotides in different cancer cell culture models using a sensitive and reproducible ion-pair HPLC method.The experimental data were analyzed by principal component analysis(PCA)to identify potential biomarkers in cancer cells,and statistical significance was determined by one-way analysis of variance.As a result,a clear differentiation of normal and tumor cells into two clusters was shown,indicating abnormal metabolism of nucleotides in tumor cells.Six variables(AMP,UDP,CTP levels with a significance of Po0.05;ATP,UTP and GMP levels with a significance of Po0.01)were considered as potential biomarkers;the content of AMP,UTP,GMP and ATP was significantly higher in cancer cells.The receiver operating characteristic(ROC)curve analysis allowed us to discriminate normal cells from tumor cells based on area under the curve(AUC).The sequence of their AUC values were:ATP(0.979)4UTP(0.938)4CTP¼GMP(0.896)4AMP(0.812)4UDP(0.792),so we conclude that ATP and UTP are the best potential biomarkers in tumor cells.This study may provide a valuable tool for studying minute alterations of intracellular nucleotide pools induced by anticancer/antiviral drugs,diseases or environmental factors.
基金supported by the National Science Foundation of China (Grant No. 81372474, 81602061)Science and Technology Program of Guangzhou (No. 2014J4100179)
文摘Objective： We aimed to evaluate the clinicopathologic characteristics, immunohistochemical expression and prognostic factors of patients with primary gastrointestinal stromal tumors（GISTs）.Methods： Data from 2,570 consecutive GIST patients from four medical centers in China（January2001–December 2015） were reviewed. Survival curves were constructed by the Kaplan-Meier method, and Cox regression models were used to identify independent prognostic factors.Results： Of the included patients, 1,375（53.5%） were male, and the patient age range was 18 to 95（median, 58）years. The tumors were mostly found in the stomach（64.5%）, small intestine（25.1%） and colorectal region（5.1%）.At the time of diagnosis, the median tumor size was 4.0（range： 0.1–55.0） cm, and the median mitotic index per 50 high power fields（HPFs） was 3（range： 0–254）. Of the 2,168 resected patients, 2,009（92.7%） received curative resection. According to the modified National Institutes of Health（NIH） classification, 21.9%, 28.9%, 14.1% and35.1% were very low-, low-, intermediate-and high-risk tumors, respectively. The rate of positivity was 96.4% for c-Kit, 87.1% for CD34, 96.9% for delay of germination 1（DOG-1）, 8.0% for S-100, 31.0% for smooth muscle actin（SMA） and 5.1% for desmin. However, the prognostic value of each was limited. Multivariate analysis showed that age, tumor size, mitotic index, tumor site, occurrence of curative resection and postoperative imatinib were independent prognostic factors. Furthermore, we found that high-risk patients benefited significantly from postoperative imatinib（P〈0.001）, whereas intermediate-risk patients did not（P=0.954）.Conclusions： Age, tumor size, mitotic index, tumor site, occurrence of curative resection and postoperative imatinib were independent prognostic factors in patients with GISTs. Moreover, determining whether intermediate-risk patients can benefit from adjuvant imatinib would be of considerable interest in future studies.
基金supported in part by the National Key Research and Development Plan,China(No.2017YFB1301101)the National Natural Science Foundation of China(Nos.61673317 and 61673313)。
文摘There exist a large class of acoustic sources which have an underlying periodic phenomenon. Unlike the well-studied Bearings-Only Tracking(BOT) of an aperiodic acoustic source,this paper considers the problem of tracking a periodic acoustic source. For periodic acoustic tracking, the signal emission time is known. However, the true measurement reception time is unknown because it is corrupted by noise due to propagation delay. We augment the sensor’s signal reception time onto bearing measurements, and the information of the delay constraint is included in the original bearing measurements to compensate for the propagation delay. A Cubature Kalman Filter(CKF) is used for periodic acoustic source tracking, in which measurement prediction cannot be obtained directly because the sensor’s position at the true measurement reception time is unknown.We solve this problem by using the implicit Gauss-Helmert Sensor Model(GHSM) for estimating the sensor’s position, which consists of the sensor’s motion equation and the known measured sensor’s signal reception time equation related to the state. Then a CKF based on the GHSM(CF-GHSM) is developed for periodic acoustic tracking. Illustrative examples demonstrate that the CF-GHSM algorithm is better than other algorithms for periodic acoustic source tracking.
文摘The problem of estimation of underwater target motion parameters via bearings only is the most of ten encountered and most difficult to solve in the underwater target motion analysis.As the bearings-only target motion analysis is a nonlinear and multiextremal global optimization problem, so most classical estimation methods often lead the solution to convergence to one of the local extremes other than the global extreme, especially, when the noise of target bearing observation is added. In this paper we propose to use the Generalized Least Square method on the rough estimation of target motion parameters, and then use the Sequential Uniform Design method to gain a more precise estimation on the bases of rough estimation.The latter ensures that the result convergences to the global extreme. The algorithm based on the above two methods is profitable for the bearings-only target motion analysis even under conditions of large bearing observation error.
文摘The method for Bearings-Only Target Motion Analysis (BO-TMA) based on bearing measurements fusion of two arrays is studied. The algorithms of pseudolinear processing, extended Kalman filter and maximum likelihood estimation are presented. The results of simulation experiments show that the BO-TMA method based on association of multiple arrays not only makes contributions towards eliminating maneuvers needed by bearings-only TMA based on single array,but also improves the stabilization and global convergence for varied estimation algorithms.
基金The work was supported by the fund (2000JS24.4.1) from the State Key Lab on Ocean Acoustics andthe research fund of Ship Industry Fundamental Research.
文摘Local-linear-prediction in phase space is performed for the underwater acoustic target radiated noise. Relation curve of average prediction error versus neighboring points' number is calculated. The result is used in judging the nonlinearity of radiated noise time series, and obtaining the appropriate form and coefficients of predicting model. The line and continuous spectral component are predicted respectively. Choice of some model parameters minimizing the prediction error is also discussed.
文摘The normalized central moments are widely used in pattern recognition because of scale and translation invariance. The moduli of normalized central moments of the 1-dimensional complex range profiles are used here as feature vector for radar target recognition. The common feature extraction method for high resolution range profile obtained by using Fourier-modified direct Mellin transform is inefficient and unsatisfactory in recognition rate And. generally speaking, the automatic target recognition method based on inverse synthetic aperture radar 2-dimensional imaging is not competent for real time object identification task because it needs complicated motion compensation which is sometimes too difficult to carry out. While the method applied here is competent for real-time recognition because of its computational efficiency. The result of processing experimental data indicates that this method is good at recognition.
基金supported by the National Natural Science Foundation of China under Grant No.11374285
文摘We propose and demonstrate a scheme to smooth and shape the on-target patterns in multimode fiber lasers, which includes expanding-collimating system and lens array （LA）. A smooth pattern with flat-top and sharp-edge profiles can be obtained with the irradiation nonuniformity decreasing significantly. We analyze the effects of the parameters such as defocus distance, the tilt angles, the number of the incident fiber lasers, and the diffraction-weakened LA on the uniformity irradiation of target by numerical simulations.
文摘In the traditional research of volatile compounds, some trace-level compounds could not be identified by gas chromatography-mass spectrometry. Target and post-targeted methods were applied in the investigation of trace-level volatile compounds in fresh turf crop （Lolium perenne L.） based on gas chromatography in combination with hybrid quadrupole time-of-flight mass spectrometry. According to literatures published, a target analysis was performed by using retention index, accurate masses of characteristic ions and second-stage mass spectra （MS2 spectra）. And a series of experiments showed that low electron impact energy was beneficial to the improvement of the abundances of low abundance molecular ion peak. peak was beneficial to qualitative analysis. Totally, 60 Enhancing the abundances of low abundance molecular ion volatile compounds were identified, the great majority cornpounds of which were benzeneacetaldehyde （14.8%）, 2,5-dimethyl-pyrazine （9.6%）, and hexanal （9.3%）. Identification was complied by mass spectral search, retention index and accurate masses of characteristic ions.
基金supported by the National Key R&D Program of China(Grant Nos.2020YFE0202200 and 2017YFC1700105)the National Natural Science Foundation of China(Grant Nos.31601064,31871341,and 32088101)+1 种基金the Beijing Nova Program of China(Grant No.Z171100001117117)the State Key Laboratory of Proteomics of China(Grant No.SKLPO202010)。
文摘After decades of development,protein and peptide drugs have now grown into a major drug class in the marketplace.Target identification and validation are crucial for the discovery of protein and peptide drugs,and bioinformatics prediction of targets based on the characteristics of known target proteins will help improve the efficiency and success rate of target selection.However,owing to the developmental history in the pharmaceutical industry,previous systematic exploration of the target spaces has mainly focused on traditional small-molecule drugs,while studies related to protein and peptide drugs are lacking.Here,we systematically explore the target spaces in the human genome specifically for protein and peptide drugs.Compared with other proteins,both successful protein and peptide drug targets have many special characteristics,and are also significantly different from those of small-molecule drugs in many aspects.Based on these features,we develop separate effective genome-wide target prediction models for protein and peptide drugs.Finally,a user-friendly web server,Predictor Of Protein and Pept Ide drugs’therapeutic Targets(POPPIT)(http://poppit.ncpsb.org.cn/),is established,which provides not only target prediction specifically for protein and peptide drugs but also abundant annotations for predicted targets.
