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Cationic porphyrins with large side arm substituents as resonance light scattering ratiometric probes for specific recognition of nucleic acid G-quadruplexes
摘要： Specific G-quadruplex-probing is crucial for both biological sciences and biosensing applications. Most reported probes are focused on fluorescent or colorimetric recognition of G-quadruplexes. Herein, for the first time, we reported a new specific G-quadruplex-probing technique—resonance light scattering (RLS)-based ratiometric recognition. To achieve the RLS probing of G-quadruplexes in the important physiological pH range of 7.4-6.0, four water soluble cationic porphyrin derivatives, including an unreported octa-cationic porphyrin, with large side arm substituents were synthesized and developed as RLS probes. These RLS probes were demonstrated to work well for ratiometric recognition of G-quadruplexes with high specificity against single- and double-stranded DNAs, including long double-stranded ones. The working mechanism was speculated to be based on the RLS signal changes caused by porphyrin protonation that was promoted by the end-stacking of porphyrins on G-quadruplexes. This work adds an important member in G-quadruplex probe family, thus providing a useful tool for studies on G-quadruplex-related events concerning G-quadruplex formation, destruction and changes in size, shape and aggregation. As a proof-of-concept example of applications, the RLS probes were demonstrated to work well for label-free and sequence-specific sensing of microRNA. This work also provides a simple and useful way for the preparation of cationic porphyrins with high charges.
关键词： G-quadruplex,ratiometric recognition,microRNA sensing,resonance light scattering,cationic porphyrin
更新于2025-11-19 16:56:35
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Determination of cholic acid in body fluids by β?cyclodextrin-modified N-doped carbon dot fluorescent probes
摘要： An easy, dependable, and sensitive cholic acid activity experiment was designed based on β?cyclodextrin-modi?ed carbon dot (β?CD-CD) nanoprobes with speci?c host–guest recognizing ability and photoelectron transfer capability. The β?CD-CD nanoprobes were characterized by infrared, ultraviolet-visible, and ?uorescence spectroscopy and transmission electron microscopy. The ?uorescence of the probes under optimized conditions linearly responded to cholic acid concentration from 0 to 650 μmol·L?1 with a detection limit of 25 nmol·L?1. The probes also performed well in detecting cholic acid in serum and urine samples with an average recovery rate of 97.1%–103.4%. Thus, this study provides a reliable, rapid, and easy method of cholic acid detection in body ?uids that can be potentially applied in medical studies.
关键词： Host–guest recognition,β?cyclodextrin,Cholic acid,Photoinduced electron transfer,Carbon dots
更新于2025-11-14 17:03:37
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Optical Character Recognition System for Nastalique Urdu-Like Script Languages using Supervised Learning
摘要： There are two main techniques to convert written or printed text into digital format. The first technique is to create an image of written/printed text, but images are large in size so they require huge memory space to store, also text in image form cannot be further processed like edit, search, copy etc. The second technique is to use an Optical Character Recognition (OCR) system. OCR’s can read documents and convert manual text documents into digital text and this digital text can be processed to extract knowledge. A huge amount of Urdu language’s data is available in handwritten or in printed form that needs to be converted into digital format for knowledge acquisition. Highly cursive, complex structure, bi-directionality, and compound in nature etc. make the Urdu language too complex to obtain accurate OCR results. In this study supervised learning based OCR system is proposed for Nastalique Urdu language. The proposed system’s evaluations under variety of experimental settings apprehend 98.4 % accuracy, which is highest recognition rate ever achieved by any Urdu language OCR system. The proposed system is simple to implement especially in software front of OCR system also the proposed technique is useful for printed text as well as handwritten text and it will help for developing more accurate Urdu OCR’s software systems in the future.
关键词： Optical Character Recognition (OCR),Image Processing,Urdu Nastalique,Supervised Learning,Pattern Recognition
更新于2025-09-23 15:23:52
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[IEEE 2018 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI) - Guangzhou, China (2018.10.8-2018.10.12)] 2018 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI) - An Efficient Recognition Method for Incomplete Iris Image Based on CNN Model
摘要： The iris of the eye is a research hot spot in the field of biometric identification because of its uniqueness, non-contact and bioactivity. The incompleteness of the iris caused by the acquisition process has brought great uncertainty to the subsequent iris region segmentation and iris code matching, thereby reducing the efficiency of iris recognition. This paper describes a deep convolution neural network model with adaptive incomplete iris preprocessing mechanism. Based on the normalization of the iris image, the incomplete iris preprocessing mechanism adopts the method of making the inner circle or the outer circle. The iris region can be segmented by the line fitting and the circle fitting method for extracting as many iris features as possible. The deep convolution neural network then uses pixel coding of Irregular iris regions to complete the iris pattern classification. The model fully utilizes the characteristics of deep learning, local feature characterization and weight sharing, and realizes the problem of using large sample to compensate the incomplete feature of local feature. The experimental results show that this method has significant accuracy improvement compared with the traditional algorithms.
关键词： iris recognition,convolution neural network,iris image normalization,algorithm
更新于2025-09-23 15:23:52
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Optically active crown ether-based fluorescent sensor molecules: A mini-review
摘要： This mini‐review focuses on fluorescent optically active crown ethers (polymeric derivatives are not included) reported in the literature (according to our knowledge), of which enantiomeric recognition ability, and in some cases, also inorganic cation complexation properties, were investigated by the sensitive and versatile fluorescence spectroscopy. These crown ether‐based chemosensors contain various fluorophore signaling units such as binaphthyl, anthracene, pyrene, tryptophan, benzimidazole, terpyridine, acridine, phenazine, acridone, BODIPY, and another conjugated aromatic one.
关键词： enantiomeric recognition,complexation,fluorophore,chemosensor,chiral crown ether
更新于2025-09-23 15:23:52
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Human activity recognition via optical flow: decomposing activities into basic actions
摘要： Recognizing human activities using automated methods has emerged recently as a pivotal research theme for security-related applications. In this research paper, an optical flow descriptor is proposed for the recognition of human actions by considering only features derived from the motion. The signature for the human action is composed as a histogram containing kinematic features which include the local and global traits. Experimental results performed on the Weizmann and UCF101 databases confirmed the potentials of the proposed approach with attained classification rates of 98.76% and 70%, respectively, to distinguish between different human actions. For comparative and performance analysis, different types of classifiers including Knn, decision tree, SVM and deep learning are applied to the proposed descriptors. Further analysis is performed to assess the proposed descriptors under different resolutions and frame rates. The obtained results are in alignment with the early psychological studies reporting that human motion is adequate for the perception of human activities.
关键词： Optical flow,Motion descriptor,Action recognition,Decomposing activities
更新于2025-09-23 15:23:52
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Bioinspired Color Changing Molecular Sensor toward Early Fire Detection Based on Transformation of Phthalonitrile to Phthalocyanine
摘要： The fire detection plays a critical role in the maintenance of public security. Previous approaches of early fire warning, based on smoke or temperature response must be set in the proximity of a fire. They cannot provide the additional information of fire location or size and are susceptible to complicated situations. It is still a big challenge to make rapid and accurate early fire warning in precombustion because of the lack of reliable alarm signals. Herein, a precursor molecular sensor (PMS) is designed and synthesized that can present the chemical structure transformation to form phthalocyanines (Pcs) and release a color change signal at about 180 °C, learning from the plant chlorophyll metabolism. Further, the PMS is assembled to an early fire warning component (EWC) and an intelligent image recognition algorithm is introduced for unburned fire detection. The EWC generates a colorful alarm within 20 s at 275 °C. Therefore, the facile PMS provides a reliable real-time monitoring strategy to the early fire warning detection in precombustion.
关键词： color change,molecular sensor,image recognition algorithm,phthalocyanine,early fire detection
更新于2025-09-23 15:23:52
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Evaluation of the temperature pattern of a complex body from thermal imaging and 3D information: A method and its MATLAB implementation
摘要： The standard setting of a camera used in Infrared thermography (IRT) is based on the choice of the same values of emissivity and distance for all pixels of a thermal image even if the emissivity depends on the relative position of camera and observed surface. Often this is not a problem. However, the resulting temperature pattern could be inadequate if a body having a complex shape is observed from strongly constrained positions. In order to face this issue, a procedure aimed at providing a correct temperature pattern by using 3D information related to a point cloud is proposed together with its MATLAB implementation (COMAP3 toolbox). For each pixel of a thermal image, the relative position of camera and observed surface is estimated, leading to pixel-specific values of emissivity and distance. The temperature obtained in this way is also mapped onto the point cloud. The effectiveness of the procedure in recognizing areas characterized by peculiar thermal behavior is shown in the case of a historic cylindrical masonry bell tower (Caorle’s bell tower, Venice, Italy).
关键词： Damage recognition,3D thermography,In situ measurements,Thermal imaging,Radiometric JPEG image
更新于2025-09-23 15:23:52
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Biometric iris recognition using radial basis function neural network
摘要： The consistent and efficient method for the identification of biometrics is the iris recognition in view of the fact that it has richness in texture information. A good number of features performed in the past are built on handcrafted features. The proposed method is based on the feed-forward architecture and uses k-means clustering algorithm for the iris patterns classification. In this paper, segmentation of iris is performed using the circular Hough transform that realizes the iris boundaries in the eye and isolates the region of iris with no eyelashes and other constrictions. Moreover, Daugman's rubber sheet model is used to transform the resultant iris portion into polar coordinates in the process of normalization. A unique iris code is generated by log-Gabor filter to extract the features. The classification is achieved using neural network structures, the feed-forward neural network and the radial basis function neural network. The experiments have been conducted using the Chinese Academy of Sciences Institute of Automation (CASIA) iris database. The proposed system decreases computation time, size of the database and increases the recognition accuracy as compared to the existing algorithms.
关键词： Feed-forward neural network (FNN),Iris segmentation,Normalization,Biometrics,Radial basis function neural network (RBFNN),Iris recognition
更新于2025-09-23 15:23:52
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A magnetic and carbon dot based molecularly imprinted composite for fluorometric detection of 2,4,6-trinitrophenol
摘要： A magnetic molecularly imprinted composite was prepared by reverse microemulsion using carbon dots (CDs), Fe3O4 as the co-nucleus, and a molecularly imprinted polymer (MIP; with 2,4,6-trinitrophenol as the template) acting as recognition sites. The composite of type CD/Fe3O4@MIPs was characterized by transmission electron microscopy (TEM), energy dispersive spectroscopy (EDS), Fourier transform infrared spectroscopy (FT-IR), zeta potentiometric analysis, X-ray diffraction (XRD) and vibrating sample magnetometry (VSM). The results showed that the composite MIP has a spherical shape with average diameter of 200 nm. They also showed that the composite contains core-shell structures with several Fe3O4 nanoparticles and CDs embedded in each of the microsphere. The composite can extract 2,4,6-trinitrophenol (TNP) and has an imprinting factor of 3.6. It has high selectivity and sensitivity for TNP which acts as a quencher of the fluorescence of the CDs (with excitation/emission maxima at 370/470 nm). The limit of detection of this fluorometric TNP assay is 0.5 nM. The method was successfully applied to the determination of TNP in spiked tap water and river water samples, and recoveries ranged from 89.4% to 108.5% (with an RSD of <6%).
关键词： Fluorescence quenching,Fe3O4 nanoparticles,Stern-Volmer plot,Environmental pollutants,Reverse microemulsion method,Selective recognition,Molecularly imprinting
更新于2025-09-23 15:23:52