- 标题
- 摘要
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- 实验方案
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Combination of Electrospray Deposition Technology of TiO2 Nanoparticles and MALDI FTICR MSI for Identification of Fingerprint Morphology and Latent Components
摘要： In fingerprint recognition, besides the physical shape information afforded by fingerprint enhancement techniques (FET), in recent years, more and more efforts are focused on researching the chemical composition of a fingerprint residue. In this work, electrospray deposition method was elaborately used to softly and homogenously deposit the physical enhancers of FET, TiO2 nanoparticles (TiO2 NPs), onto fingerprints. The results showed that this type of deposition was nondestructive to the fingerprint morphology and provided the physical shape information containing all level features. Concurrently, the TiO2 NPs demonstrated as a better matrix of matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI MSI) for analysis and imaging of latent components in fingerprint, including endogenous substances like triacylglycerols (TAGs), diacylglycerols (DAGs) and cholesterol esters (CEs), and exogenous substances such as certain ingredients in hand lotion. The chemical compositions in fingerprint are closely related to individual metabolites and individual lifestyles, and identification of these compositions by Fourier transform ion cyclotron resonance (FTICR) MS is extremely beneficial for forensic analysis. The combinations of electrospray deposition technology of TiO2 NPs and MALDI FTICR MSI for identification of fingerprint morphology and latent components provide dual-modes fingerprint recognition for forensic science.
关键词： Fingerprint recognition,Electrospray deposition,MALDI-FTICR MSI,Physical enhancement,TiO2 nanoparticles
更新于2025-09-19 17:15:36
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Electroactive Au@Ag NP Assemblies Driven Signal Amplification for Ultrasensitive Chiral Recognition of D-/L-Trp
摘要： A novel ingenious and ultrasensitive chiral electrochemical transducer is proposed for the tryptophan (Trp) isomers detection by using electroactive Au@Ag NPs as electrochemical tags. Moreover, the large binding constant of D-Trp on NPs and strong interaction between D-Trp and Cu2+ cause electroactive Au@Ag NP to assembly on the electrode, generating strong differential pulse voltammetry (DPV) signals from the oxidation of Ag0 to Ag+. In sharp contrast to D-Trp, L-Trp leads to the assembly of Au@Ag NP oligomers on electrode, resulting in a weak DPV signal. The distinct DPV responses enable the developed electrochemical chiral transducer for the sensitive and accurate quantification of D-/L-Trp. The limit of detection (LOD) is 1.21 pM for D-Trp. This established electrochemical chiral sensor also achieves the specific determination of enantiomeric excess. In comparison to other reported approaches, this proposed electrochemical chiral sensor excels by its sensitivity, simplicity and good availability of electroactive Au@Ag NP assemblies. Target-induced colorimetric assays can be converted into electrochemical assays for the dual signal amplification in the field of ultrasensitive enantioselective chiral discrimination.
关键词： Au@Ag NPs,Chiral recognition,Trp enantiomers,Electroactive,Assemblies
更新于2025-09-19 17:15:36
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Molecular design for novel sensing materials with self-screening interference effect (SSIE): Reversible recognizing Cu2+ in aqueous and biologic samples
摘要： In the work, self-screening interference effect (SSIE) was proposed for sensing trace Cu2+ by simply thermodynamic control reactions, using dipyridine as self-screening interference group, rhodamine as mother chromophore and cyanuric chloride as connecting bridge. After its UV-vis and fluorescent spectral properties were optimized in detail, it was noted to find that the present sensing material (RACD) could selectively and reversibly react Cu2+ with obvious colorimetric or fluorescent spectral and color changes from colorless to pink or orange-red. Some other concomitant ions, even trivalent Fe3+ or Al3+, had no interferences on it. Under the optimized conditions, RACD could multiple-mode sense trace Cu2+ in aqueous with a detection limit as low as 11.0 nmol/L. Especially with low toxicity, RACD was successfully applied for quantitatively monitoring Cu2+ and evaluating its toxicity in living cells and bio-tissues. RACD-functionalized paper-strips were also prepared to visibly recognize Cu2+ more conveniently. The selective action mechanism for RACD to Cu2+ was to form some stable 5-membered and 5-membered condensed rings between Cu2+ and O or N atoms.
关键词： Self-screening interference effect (SSIE),Tumor-bearing mice,Recognition mechanism,Trace Cu2+,Cyanuric-bridge multi-chelate,Reversibly sensing
更新于2025-09-19 17:15:36
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Identification of Bacteria by a Fluorescence Sensor Array based on Three Kinds of Receptors Functionalized Carbon Dots
摘要： The identification of bacteria is a crucial issue in the field of medical diagnosis, environmental monitoring and food safety. Conventional methods need long culturing times, highly skilled operators, or recognition elements specific to each kind of the bacteria. Alternatively, sensor arrays offer a cost-effective and simple approach using multiple cross-reactive receptors. Here, a facilely constructed fluorescence sensing array was developed for the identification of various bacteria. The sensor array consists of three facile synthesized carbon dots functionalized with different receptors (boronic acid, polymixin and vancomycin), which could bind to all the bacteria with different affinity instead of a specific one. A unique molecular fingerprint of each kind of bacteria was obtain from the fluorescence response pattern generated from three kinds of carbon dots. By using linear discrimination analysis (LDA) of the response pattern, the effective discrimination of six bacteria studied was demonstrated. The proposed sensor array approach may pave the way for the development of simple, rapid and effective identification of multiplex bioactive samples.
关键词： bacterial identification,cross-reactive receptors,carbon dots,pattern recognition,sensor array
更新于2025-09-19 17:15:36
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Postmetallization a??Passivated Edge Technologya?? for Separated Silicon Solar Cells
摘要： Features for speech emotion recognition are usually dominated by the spectral magnitude information while they ignore the use of the phase spectrum because of the difficulty of properly interpreting it. Motivated by recent successes of phase-based features for speech processing, this paper investigates the effectiveness of phase information for whispered speech emotion recognition. We select two types of phase-based features (i. e., modified group delay features and all-pole group delay features), both which have shown wide applicability to all sorts of different speech analysis and are now studied in whispered speech emotion recognition. When exploiting these features, we propose a new speech emotion recognition framework, employing outer product in combination with power and L2 normalization. The according technique encodes any variable length sequence of the phase-based features into a fixed dimension vector regardless of the length of the input sequence. The resulting representation is fed to train a classification model with a linear kernel classifier. Experimental results on the Geneva Whispered Emotion Corpus database, including normal and whispered phonation, demonstrate the effectiveness of the proposed method when compared with other modern systems. It is also shown that, combining phase information with magnitude information could significantly improve performance over the common systems solely adopting magnitude information.
关键词： whispered speech emotion recognition,Phase-based features,outer product
更新于2025-09-19 17:13:59
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A Global Maximum Power Point Tracking Algorithm for Photovoltaic Systems Under Partially Shaded Conditions Using Modified Maximum Power Trapezium Method
摘要： This paper is about how the SP theory of intelligence and its realization in the SP machine (both outlined in this paper) may help in the design of the brains of autonomous robots, meaning robots that do not depend on external intelligence or power supplies, are mobile, and have human-like versatility and adaptability in intelligence. This paper addresses three main problems: 1) how to increase the computational and energy efficiency of computers and to reduce their size and weight; 2) how to achieve human-like versatility in intelligence; and 3) likewise for human-like adaptability in intelligence. Regarding the first problem, the SP system has the potential for substantial gains in computational efficiency, with corresponding cuts in energy consumption and the bulkiness of computers: 1) by reducing the size of data to be processed; 2) by exploiting statistical information that the system gathers as an integral part of how it works; and 3) via a new version of Donald Hebb’s concept of a cell assembly. Toward human-like versatility in intelligence, the SP system has strengths in unsupervised learning, natural language processing, pattern recognition, information retrieval, several kinds of reasoning, planning, problem solving, and more, with seamless integration among structures and functions. The SP system’s strengths in unsupervised learning and other aspects of intelligence may help in achieving human-like adaptability in intelligence via: 1) one-trial learning; 2) learning of natural language; 3) learning to see; 4) building 3-D models of objects and of a robot’s surroundings; 5) learning regularities in the workings of a robot and in the robot’s environment; 6) exploration and play; 7) learning major skills; and 8) learning via demonstration. Also discussed are how the SP system may process parallel streams of information, generalization of knowledge, correction of over-generalizations, learning from dirty data, how to cut the cost of learning, and reinforcements and motivations.
关键词： data compression,pattern recognition,robots,unsupervised learning,Artificial intelligence,cognitive science
更新于2025-09-19 17:13:59
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[IEEE 2019 44th International Conference on Infrared, Millimeter, and Terahertz Waves (IRMMW-THz) - Paris, France (2019.9.1-2019.9.6)] 2019 44th International Conference on Infrared, Millimeter, and Terahertz Waves (IRMMW-THz) - A Gap Waveguide Fed Circular Polarization Antenna in the Millimeter-Wave Range
摘要： Due to its wide applications in practice, face recognition has been an active research topic. With the availability of adequate training samples, many machine learning methods could yield high face recognition accuracy. However, under the circumstance of inadequate training samples, especially the extreme case of having only a single training sample, face recognition becomes challenging. How to deal with con?icting concerns of the small sample size and high dimensionality in one-sample face recognition is critical for its achievable recognition accuracy and feasibility in practice. Being different from the conventional methods for global face recognition based on generalization ability promotion and local face recognition depending on image segmentation, a single-sample face recognition algorithm based on locality preserving projection (LPP) feature transfer is proposed here. First, transfer sources are screened to obtain the selective sample source using the whitened cosine similarity metric. Second, we project the vectors of source faces and target faces into feature subspace by LPP, respectively, and calculate the feature transfer matrix to approximate the mapping relationship on source faces and target faces in subspace. Then, the feature transfer matrix is used on training samples to transfer the original macro characteristics to target macro characteristics. Finally, the nearest neighbor classi?er is used for face recognition. Our results based on popular databases FERET, ORL, and Yale demonstrate the superiority of the proposed LPP feature transfer-based one-sample face recognition algorithm when compared with popular single-sample face recognition algorithms, such as (PC)2A and Block FLDA.
关键词： one-sample,Feature extraction,face recognition,locality preserving projection,transfer learning
更新于2025-09-19 17:13:59
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Single-Layer Mode Composite Coplanar Waveguide Dual-Band Filter With Large Frequency Ratio
摘要： Grasping and manipulating everyday objects in a goal-directed manner is an important ability of a service robot. The robot needs to reason about task requirements and ground these in the sensorimotor information. Grasping and interaction with objects are challenging in real-world scenarios, where sensorimotor uncertainty is prevalent. This paper presents a probabilistic framework for the representation and modeling of robot-grasping tasks. The framework consists of Gaussian mixture models for generic data discretization, and discrete Bayesian networks for encoding the probabilistic relations among various task-relevant variables, including object and action features as well as task constraints. We evaluate the framework using a grasp database generated in a simulated environment including a human and two robot hand models. The generative modeling approach allows the prediction of grasping tasks given uncertain sensory data, as well as object and grasp selection in a task-oriented manner. Furthermore, the graphical model framework provides insights into dependencies between variables and features relevant for object grasping.
关键词： learning and adaptive systems,recognition,probabilistic graphical models,grasping,Cognitive human–robot interaction
更新于2025-09-19 17:13:59
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An image segmentation algorithm based on double-layer pulse-coupled neural network model for kiwifruit detection
摘要： Finding a universal and accurate image segmentation algorithm for kiwifruit detection under varying illumination and complex background has become one of the most challenging problems in machine vision research. In this study, a robust segmentation algorithm based on a double-layer pulse-coupled neural network (PCNN) model is proposed. First of all, an improved PCNN merged with the image frequency-tuned saliency is devised as a basic structure. Secondly, in the red-green-blue color mode, the optimal color-difference information of a kiwifruit image is determined in the first layer of this double-layer PCNN. Then, enhanced hue features are fused with these optimal color-difference features by the total variation model. Finally, the target regions are built by the re-segmentation of the second layer of this double-layer PCNN. Experimental results demonstrate that the proposed algorithm significantly outperforms the typical existing algorithms in terms of the subjective visual effect and the objective quantitative evaluation.
关键词： Kiwifruit recognition,Pulse-coupled neural network,Frequency-tuned saliency,Total variation model,Image segmentation
更新于2025-09-19 17:13:59
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Solar-stimulated optoelectronic synapse based on organic heterojunction with linearly potentiated synaptic weight for neuromorphic computing
摘要： We report an artificial optoelectronic synapse based on a copper-phthalocyanine (CuPc) and para-sexiphenyl (p-6P) heterojunction structure. This device features stable conductance states and their linear distribution in long-term potentiation (LTP) characteristic curve formed by continuous input light pulses. These superior synaptic characteristics originate from the fact that the number of photo-holes moving into the CuPc channel and photo-electrons being trapped at the p-6P/dielectric interface is constant at every light pulse. A single-layer neural network is theoretically formed with these optoelectronic synaptic devices and its feasibility is studied in terms of training/recognition tasks of the Modified National Institute of Standards and Technology digit image patterns. Owing to the excellent LTP characteristic and through the use of a unidirectional update method, its maximum recognition rate is as high as 78% despite the use of a single-layer network. This study is expected to provide a foundation for future studies on optoelectronic synaptic devices toward the implementation of complex artificial neural networks.
关键词： Solar-stimulated optoelectronic synapse,Neuromorphic computing,Band engineering,Pattern recognition,Organic heterojunction
更新于2025-09-19 17:13:59