The first record of abnormal body coloration in Sebastes koreanus Kim and Lee,1994,from the Yellow Sea of China,was documented based on morphological characteristics and DNA barcoding.The two rockfish specimens were c...The first record of abnormal body coloration in Sebastes koreanus Kim and Lee,1994,from the Yellow Sea of China,was documented based on morphological characteristics and DNA barcoding.The two rockfish specimens were collected from the coastal waters of Qingdao,China,and the whole body and all fins of them were red.Of the two red-colored rockfish,there were tiny deep red spots on each fin,2 red radial stripes behind and below the eyes and 1 large deep red blotch on the opercula,while the similar stripe and spot patterns are also present in the S.koreanus specimens with normal body coloration.The countable characteristics of the two specimens are in the range of the morphometry of S.koreanus.To further clarify the species identity and taxonomic status of the two specimens,DNA barcode analysis was carried out.The genetic distance between the red-colored rockfish and S.koreanus was 0,and the minimum net genetic distances between the red-colored rockfish and other Sebastes species except for S.koreanus were 3.0%,which exceeds the threshold of species delimitation.The phylogenetic analysis showed that the DNA barcoding sequences of the two red-colored rockfish clustered with the S.koreanus sequences.The above results of DNA barcode analysis also support that the two red-colored rockfish could be identified as the species of S.koreanus.The mechanism of color variation in S.koreanus is desirable for further research and the species could be an ideal model to study the color-driven speciation of the rockfishes.展开更多
A novel color image encryption scheme is developed to enhance the security of encryption without increasing the complexity. Firstly, the plain color image is decomposed into three grayscale plain images, which are con...A novel color image encryption scheme is developed to enhance the security of encryption without increasing the complexity. Firstly, the plain color image is decomposed into three grayscale plain images, which are converted into the frequency domain coefficient matrices(FDCM) with discrete cosine transform(DCT) operation. After that, a twodimensional(2D) coupled chaotic system is developed and used to generate one group of embedded matrices and another group of encryption matrices, respectively. The embedded matrices are integrated with the FDCM to fulfill the frequency domain encryption, and then the inverse DCT processing is implemented to recover the spatial domain signal. Eventually,under the function of the encryption matrices and the proposed diagonal scrambling algorithm, the final color ciphertext is obtained. The experimental results show that the proposed method can not only ensure efficient encryption but also satisfy various sizes of image encryption. Besides, it has better performance than other similar techniques in statistical feature analysis, such as key space, key sensitivity, anti-differential attack, information entropy, noise attack, etc.展开更多
The desert plant Rhazya stricta has anticancer and antimicrobial properties, and is widely used in indigenous medicines of Saudi Arabia. However, the therapeutic benefits rely on an accurate identification of this spe...The desert plant Rhazya stricta has anticancer and antimicrobial properties, and is widely used in indigenous medicines of Saudi Arabia. However, the therapeutic benefits rely on an accurate identification of this species. The authenticity of R. stricta and other medicinal plants and herbs procured from local markets can be questionable due to a lack of clear phenotypic traits. DNA barcoding is an emerging technology for rapid and accurate species identification. In this study, six candidate chloroplastid barcodes were investigated for the authentication of R. stricta. We compared the DNA sequences from fifty locally collected and five market samples of R. stricta with database sequences of R. stricta and seven closely related species. We found that the coding regions matK, rbcL, rpoB, and rpoC1 were highly similar among the taxa. By contrast, the intergenic spacers psbK-psbI and atpF-atpH were variable loci distinct for the medicinal plant R. stricta. psbK-psbI clearly discriminated R. stricta samples as an efficient single locus marker, whereas a two-locus marker combination comprising psbK-psbI + atpF-atpH was also promising according to results from the Basic Local Alignment Search Tool and a maximum likelihood gene tree generated using PHyML. Two-dimensional DNA barcodes (i.e., QR codes) for the psbK-psbI and psbK-psbI + atpF-atpH regions were created for the validation of fresh or dried R. stricta samples.展开更多
To investigate the chemical transformation of volatile compounds in sulfur-fumigated Radix Angelicae Sinensis. A comprehensive two-dimensional gas chromatography (GCxGC) and high-resolution time-of-flight mass spectro...To investigate the chemical transformation of volatile compounds in sulfur-fumigated Radix Angelicae Sinensis. A comprehensive two-dimensional gas chromatography (GCxGC) and high-resolution time-of-flight mass spectrometry (HR-TOF/MS) with colorized fuzzy difference (CFD) method was used to investigate the effect of sulfur-fumigation on the volatile components from Radix Angelicae Sinensis. Twenty-five compounds that were found in sun-dried samples disappeared in sulfur-fumigated samples. Seventeen volatile components including two sulfur-containing compounds were newly generated for the first time in volatile oils of sulfur-fumigated Radix Angelicae Sinensis. The strategy can be successfully applied to rapidly and holistically discriminate sun-dried and sulfur-fumigated Radix Angelicae Sinensis. GCxGC-HR-TOF/MS based CFD is a powerful and feasible approach for the global quality evaluation of Radix Angelicae Sinensis as well as other herbal medicines.展开更多
A combination of Fresnel law and machine learning method is proposed to identify the layer counts of 2D materials.Three indexes,which are optical contrast,red-green-blue,total color difference,are presented to illustr...A combination of Fresnel law and machine learning method is proposed to identify the layer counts of 2D materials.Three indexes,which are optical contrast,red-green-blue,total color difference,are presented to illustrate and simulate the visibility of 2D materials on Si/SiO_(2) substrate,and the machine learning algorithms,which are k-mean clustering and k-nearest neighbors,are employed to obtain thickness database of 2D material and test the optical images of 2D materials via red-green-blue index.The results show that this method can provide fast,accurate and large-area property of 2D material.With the combination of artificial intelligence and nanoscience,this machine learning assisted method eases the workload and promotes fundamental research of 2D materials.展开更多
基金Supported by the National Key R&D Program of China (No.2018YFD0900803)the China Agriculture Research System of MOF and MARA (No.CARS-47)the Central Public-Interest Scientific Institution Basal Research Fund (Nos.2021JC01,20603022022024)
文摘The first record of abnormal body coloration in Sebastes koreanus Kim and Lee,1994,from the Yellow Sea of China,was documented based on morphological characteristics and DNA barcoding.The two rockfish specimens were collected from the coastal waters of Qingdao,China,and the whole body and all fins of them were red.Of the two red-colored rockfish,there were tiny deep red spots on each fin,2 red radial stripes behind and below the eyes and 1 large deep red blotch on the opercula,while the similar stripe and spot patterns are also present in the S.koreanus specimens with normal body coloration.The countable characteristics of the two specimens are in the range of the morphometry of S.koreanus.To further clarify the species identity and taxonomic status of the two specimens,DNA barcode analysis was carried out.The genetic distance between the red-colored rockfish and S.koreanus was 0,and the minimum net genetic distances between the red-colored rockfish and other Sebastes species except for S.koreanus were 3.0%,which exceeds the threshold of species delimitation.The phylogenetic analysis showed that the DNA barcoding sequences of the two red-colored rockfish clustered with the S.koreanus sequences.The above results of DNA barcode analysis also support that the two red-colored rockfish could be identified as the species of S.koreanus.The mechanism of color variation in S.koreanus is desirable for further research and the species could be an ideal model to study the color-driven speciation of the rockfishes.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.62105004 and 52174141)the College Student Innovation and Entrepreneurship Fund Project(Grant No.202210361053)+1 种基金Anhui Mining Machinery and Electrical Equipment Coordination Innovation Center,Anhui University of Science&Technology(Grant No.KSJD202304)the Anhui Province Digital Agricultural Engineering Technology Research Center Open Project(Grant No.AHSZNYGC-ZXKF021)。
文摘A novel color image encryption scheme is developed to enhance the security of encryption without increasing the complexity. Firstly, the plain color image is decomposed into three grayscale plain images, which are converted into the frequency domain coefficient matrices(FDCM) with discrete cosine transform(DCT) operation. After that, a twodimensional(2D) coupled chaotic system is developed and used to generate one group of embedded matrices and another group of encryption matrices, respectively. The embedded matrices are integrated with the FDCM to fulfill the frequency domain encryption, and then the inverse DCT processing is implemented to recover the spatial domain signal. Eventually,under the function of the encryption matrices and the proposed diagonal scrambling algorithm, the final color ciphertext is obtained. The experimental results show that the proposed method can not only ensure efficient encryption but also satisfy various sizes of image encryption. Besides, it has better performance than other similar techniques in statistical feature analysis, such as key space, key sensitivity, anti-differential attack, information entropy, noise attack, etc.
文摘The desert plant Rhazya stricta has anticancer and antimicrobial properties, and is widely used in indigenous medicines of Saudi Arabia. However, the therapeutic benefits rely on an accurate identification of this species. The authenticity of R. stricta and other medicinal plants and herbs procured from local markets can be questionable due to a lack of clear phenotypic traits. DNA barcoding is an emerging technology for rapid and accurate species identification. In this study, six candidate chloroplastid barcodes were investigated for the authentication of R. stricta. We compared the DNA sequences from fifty locally collected and five market samples of R. stricta with database sequences of R. stricta and seven closely related species. We found that the coding regions matK, rbcL, rpoB, and rpoC1 were highly similar among the taxa. By contrast, the intergenic spacers psbK-psbI and atpF-atpH were variable loci distinct for the medicinal plant R. stricta. psbK-psbI clearly discriminated R. stricta samples as an efficient single locus marker, whereas a two-locus marker combination comprising psbK-psbI + atpF-atpH was also promising according to results from the Basic Local Alignment Search Tool and a maximum likelihood gene tree generated using PHyML. Two-dimensional DNA barcodes (i.e., QR codes) for the psbK-psbI and psbK-psbI + atpF-atpH regions were created for the validation of fresh or dried R. stricta samples.
基金Supported by the National Natural Science Foundation of China(No.81173546 and No.30940093)the Natural Science Foundation of Jiangsu Province,China(No.BK2009495)+4 种基金the International Science and Technology Cooperation Project of Jiangsu Province,China(No.BZ2011053)the Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD,No.2011ZYX2-001)the Postgraduate Research Innovation Project of Jiangsu Higher Education Institutions(No.KYLX_0975)the Chinese Medicine Research Program of Zhejiang Province,China(No.2014ZQ008)the Science Foundation of Zhejiang Chinese Medical University(No.2013ZZ12)
文摘To investigate the chemical transformation of volatile compounds in sulfur-fumigated Radix Angelicae Sinensis. A comprehensive two-dimensional gas chromatography (GCxGC) and high-resolution time-of-flight mass spectrometry (HR-TOF/MS) with colorized fuzzy difference (CFD) method was used to investigate the effect of sulfur-fumigation on the volatile components from Radix Angelicae Sinensis. Twenty-five compounds that were found in sun-dried samples disappeared in sulfur-fumigated samples. Seventeen volatile components including two sulfur-containing compounds were newly generated for the first time in volatile oils of sulfur-fumigated Radix Angelicae Sinensis. The strategy can be successfully applied to rapidly and holistically discriminate sun-dried and sulfur-fumigated Radix Angelicae Sinensis. GCxGC-HR-TOF/MS based CFD is a powerful and feasible approach for the global quality evaluation of Radix Angelicae Sinensis as well as other herbal medicines.
基金National Key Research and Development Program of China(2016YFA0201001)National Natural Science Foundation of China(11627801,11472130,11872203,and 11572276)+3 种基金Shenzhen Science and Technology Innovation Committee(JCYJ20170818160815002)Shenzhen Science and Technology Research Funding(JCYJ20160608141439330)Natural Science Foundation of Xinjiang(2017D01C055)Wuhan University of Technology(2018-KF-14).
文摘A combination of Fresnel law and machine learning method is proposed to identify the layer counts of 2D materials.Three indexes,which are optical contrast,red-green-blue,total color difference,are presented to illustrate and simulate the visibility of 2D materials on Si/SiO_(2) substrate,and the machine learning algorithms,which are k-mean clustering and k-nearest neighbors,are employed to obtain thickness database of 2D material and test the optical images of 2D materials via red-green-blue index.The results show that this method can provide fast,accurate and large-area property of 2D material.With the combination of artificial intelligence and nanoscience,this machine learning assisted method eases the workload and promotes fundamental research of 2D materials.
