Article
Food Science & Technology
Xinxin Zhang, Shangke Li, Yang Shan, Pao Li, Liwen Jiang, Xia Liu, Wei Fan
Summary: This study uses a near-infrared diffuse reflectance spectroscopy system to accurately determine the soluble solids content of citrus without causing damage. The results show that the NIRDRS light can penetrate the thick peel to some extent, and the selection of specific characteristic variables can improve the accuracy of the quantitative analysis models with fewer variables.
JOURNAL OF FOOD PROCESSING AND PRESERVATION
(2022)
Article
Engineering, Multidisciplinary
Jin Li, Xinyuan Xing, Xiangdao Hou, Tao Wang, Jiayu Wang, Feipeng Xiao
Summary: This study proposes a rapid and accurate method for determining SARA fractions in petroleum asphalts using MIR spectra and PLSR modeling. It successfully prepares asphalt samples with different SARA fractions through blending and progressive aging process. By measuring and collecting the SARA fractions and MIR spectra of these samples, quantitative calibration models are developed using the MIR spectra and PLSR method. The results show high consistency between the measured and predicted values, indicating the method's reproducibility and repeatability. This MIR-PLSR method can provide faster SARA determination than standard test methods, making it applicable for real-time quality control and in-situ inspection of asphalt materials in road construction.
Article
Chemistry, Analytical
Katarzyna Wlodarska, Pawel Piasecki, Ana Lobo-Prieto, Katarzyna Pawlak-Lemanska, Tomasz Gorecki, Ewa Sikorska
Summary: This study evaluated and compared the potential of different optical spectroscopic techniques for quality assessment of apple juices. Calibration models based on NIR spectra of fruit showed high predictive ability for certain quality parameters, while models based on juice spectra performed best for others. The results provide insights for the development of fast quality control methods for juices.
MICROCHEMICAL JOURNAL
(2021)
Article
Chemistry, Analytical
Etil Guzelmeric, Durmus Ozdemir, Nisa Beril Sen, Cansel Celik, Erdem Yesilada
Summary: The plant source of propolis determines its chemical composition, which can be identified and quantified using HPTLC and HPLC techniques. This study compared the amounts of marker components in propolis samples using HPTLC images and validated HPLC methods, and successfully demonstrated the feasibility of quantifying propolis using HPTLC images.
JOURNAL OF PHARMACEUTICAL AND BIOMEDICAL ANALYSIS
(2023)
Article
Chemistry, Applied
Ulisses F. Oliveira, Annanda M. Costa, Jussara Roque, Wilson Cardoso, Sergio Y. Motoike, Marcio H. P. Barbosa, Reinaldo F. Teofilo
Summary: A method for early quantification of unripe macaw fruits oil content using near-infrared spectroscopy and partial least squares was proposed, which could accurately predict the oil content within 30 days after fruit harvest, thus reducing the costs of quality control and storage for macaw palm.
Article
Chemistry, Analytical
Yiming Bi, Xianwei Hao, Lu Dai, Yuhan Peng, Jinxin Tie, Yunong Tian, Fu Liao, Yongsheng Li, Wenmiao He, Shitou Li, Lili Zhang, Zhenjie Zhao, Jizhong Wu, Hui Wang
Summary: The study introduces a novel variable selection method that requires no reference information, utilizing replicate spectra and an index to evaluate variable importance. It outperforms the original partial least squares model with limited calibration samples, and shows comparable results to state-of-the-art methods with a large number of calibration samples while reducing the risk of overfitting.
ANALYTICAL LETTERS
(2022)
Article
Agricultural Engineering
M. I. S. Verissimo, C. Soares, C. F. Moreirinha, M. T. S. R. Gomes
Summary: In this study, a method based on NIR spectroscopy was used to predict the pour point and ethanol content of biodiesel mixtures. The results showed that this method has good prediction capability and is faster and more convenient compared to the traditional ASTM D97-08 procedure.
BIOMASS & BIOENERGY
(2023)
Article
Chemistry, Applied
Jonas Simon, Otgontuul Tsetsgee, Nohman Arshad Iqbal, Janak Sapkota, Matti Ristolainen, Thomas Rosenau, Antje Potthast
Summary: The properties of dialdehyde celluloses are highly dependent on the aldehyde content, and the current methods for determining the aldehyde content lack simplicity and speed. This study proposes a new approach using near-infrared and Fourier-transform infrared spectroscopy, combined with partial least squares regression, to quickly and reliably predict the aldehyde content of dialdehyde celluloses.
CARBOHYDRATE POLYMERS
(2022)
Article
Spectroscopy
Yong Hao, Yuanhang Lu, Xiyan Li
Summary: In this study, a stability monitor model was established using the multivariate statistical process control (MSPC) method, and a mixed modeling approach combining robust regression (Rob-Reg) and partial least squares regression (PLSR) was employed to eliminate the variability influence of sample and instrument states. The results showed that MSPC effectively monitored the consistency of the same batch samples measured at different times or different batches, and the Rob-Reg method outperformed the PLSR method in predicting the different batches of samples.
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
(2022)
Article
Biochemical Research Methods
Ruoyu Tang, Xinyu He, Ruiqi Wang
Summary: The study presents a general computational method for constructing maps between different cell fates and parametric conditions by systematic perturbations. The method does not require accurate parameter measurements or bifurcations. The maps obtained can help in understanding how systematic perturbations drive cell fate decisions and transitions, providing valuable information for predicting and controlling cell states.
Article
Forestry
Michael S. Watt, David J. Palmer, Ellen Mae C. Leonardo, Maxime Bombrun
Summary: Site productivity indices have been widely used to describe age-normalized height and volume of forest species. In this study, a variety of modeling methods were used to predict Site Index and 300 Index for Pinus radiata D. Don, with non-parametric models like eXtreme Gradient Boosting and random forest outperforming parametric and geospatial models. The use of regression kriging improved prediction accuracy, especially for parametric models, and an ensemble model combining predictions from random forest, XGBoost, and regression model provided the most precise predictions for both Site Index and 300 Index.
FOREST ECOLOGY AND MANAGEMENT
(2021)
Article
Agricultural Engineering
Gaixiu Yang, Ying Li, Feng Zhen, Yonghua Xu, Jinming Liu, Nan Li, Yong Sun, Lina Luo, Ming Wang, Lingling Zhang
Summary: The study found that the regression model based on characteristic wavelengths selected by NIRS showed superior performance in predicting biochemical methane potential. The predicted accuracy of the NIRS model was very high, meeting the requirements for rapid prediction of BMP for co-AD feedstocks in practical biogas engineering.
BIORESOURCE TECHNOLOGY
(2021)
Article
Automation & Control Systems
Peng Shan, Yuhui Zhao, Qiaoyun Wang, Shuyu Wang, Yao Ying, Silong Peng
Summary: The proposed nonlinear strategy reconstructs the feature representation of master/slave spectra in RKHS using SVD, aiming at minimizing instrument-induced spectral variations and transferring features between master and slave spectra. The KPLS model built on the transferred features shows good performance in multivariate calibration, outperforming several existing calibration transfer methods on spectral datasets.
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
(2021)
Article
Engineering, Chemical
Chrysoula D. Kappatou, James Odgers, Salvador Garcia-Munoz, Ruth Misener
Summary: This study investigates the coupling of preprocessing and model parameter estimation, incorporating them simultaneously in an optimization step to examine their impact on regression model and its predictive ability. The authors introduce a novel mathematical definition for model robustness, optimizing for both model accuracy and robustness. The results demonstrate the importance of both accuracy and robustness properties and show the potential of the proposed optimization approach in automating the generation of efficient chemometric models.
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
(2023)
Article
Chemistry, Analytical
Forrest D. Heller, Laura R. H. Ahlers, Zoe E. Nordquist, Navindra H. Gunawardena, Amanda D. French, Amanda M. Lines, Gilbert L. Nelson, Amanda J. Casella, Samuel A. Bryan
Summary: Online spectroscopic measurements are useful for providing unique insights into complex chemical systems, such as monitoring the pH of acid systems in real-time. This study used Raman spectroscopy to characterize acids used in various chemical separation processes and developed a consolidated model scheme to measure the pH of weak acid systems. The results showed that the Raman-based approach accurately analyzed weak acid solution pH.
ANALYTICAL CHEMISTRY
(2022)
Article
Engineering, Electrical & Electronic
Xiyuan Hu, Silong Peng, Baokui Guo, Pengcheng Xu
Summary: In this paper, we propose a novel adaptive nonparametric regularization method for solving optimization problems with linear constraint, and introduce a new differential operator to eliminate AM-FM signals. Experimental results demonstrate that the proposed methods are more effective and robust in signal demodulation and separation.
Article
Chemistry, Analytical
Peng Shan, Zhigang Li, Qiaoyun Wang, Zhonghai He, Shuyu Wang, Yuhui Zhao, Zhui Wu, Silong Peng
Summary: In this study, a novel standard-free model adaption method called VSSOM was proposed, utilizing self-organizing maps and variable selection strategy to achieve stable selection of feature subsets across different batches with superior and comparable prediction performance.
ANALYTICA CHIMICA ACTA
(2021)
Article
Chemistry, Analytical
Genwei Zhang, Silong Peng, Jie Yang, Shuya Cao, Qibin Huang
Summary: This study presents an asymmetric peak model for processing ion mobility peaks to extract characteristic analyte peaks and achieve online qualitative analysis. By focusing on the Coulombic effects, a new hypothesis of ion cloud shape was proposed, and a formula for calculating the standard deviation was derived. The proposed method successfully decomposed overlapping peaks into individual peaks and outperformed other available methods in terms of execution time.
ANALYTICA CHIMICA ACTA
(2021)
Article
Chemistry, Analytical
Yiming Bi, Xianwei Hao, Lu Dai, Yuhan Peng, Jinxin Tie, Yunong Tian, Fu Liao, Yongsheng Li, Wenmiao He, Shitou Li, Lili Zhang, Zhenjie Zhao, Jizhong Wu, Hui Wang
Summary: The study introduces a novel variable selection method that requires no reference information, utilizing replicate spectra and an index to evaluate variable importance. It outperforms the original partial least squares model with limited calibration samples, and shows comparable results to state-of-the-art methods with a large number of calibration samples while reducing the risk of overfitting.
ANALYTICAL LETTERS
(2022)
Article
Computer Science, Artificial Intelligence
Xiaolian Wang, Xiyuan Hu, Chen Chen, Silong Peng
Summary: Localization is a critical subtask in object detection, and this work proposes a method to improve localization performance on small datasets by fully exploiting limited annotations. By extracting label geometry and generating distance transform, the method reconstructs object geometry through pixel-wise supervision, and enhances geometric-aware features through coupled training with regression.
PATTERN RECOGNITION LETTERS
(2022)
Correction
Computer Science, Artificial Intelligence
Wen Qian, Zhiqun He, Chen Chen, Silong Peng
Article
Computer Science, Artificial Intelligence
Wen Qian, Zhiqun He, Chen Chen, Silong Peng
Summary: This paper introduces how to mine discriminative and fine-grained information in the field of re-identification through a multi-branch architecture. It proposes partner learning and hierarchical structural knowledge transfer methods, and designs two local specifications to effectively extract more clues.
Article
Engineering, Electrical & Electronic
Wen Qian, Xue Yang, Silong Peng, Xiujuan Zhang, Junchi Yan
Summary: In this paper, we propose a novel method for detecting rotation sensitivity errors (RSE) by introducing a modulated rotation loss to mitigate performance degradation. The proposed method achieves competitive results in rotated object detection and effectively detects tiny objects.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
(2022)
Article
Engineering, Civil
Wen Qian, Zhiqun He, Chen Chen, Silong Peng
Summary: This paper proposes a novel Salience-Navigated Vehicle Re-identification Network (SVRN) that explores diverse salient features at multi-scales. It tackles the limitation of traditional methods by mining sufficient salient features. Extensive experiments demonstrate its effectiveness and show superior results compared to previous state-of-the-art methods.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Multidisciplinary Sciences
Md. Arju Hossain, Md Sohel, Md Habibur Rahman, Md Imran Hasan, Md. Sharif Khan, Md. Al Amin, Md. Zahidul Islam, Silong Peng
Summary: Despite modern treatment, infertility remains a common gynecologic disease with severe health effects worldwide. Cancerous risk factors have been found to be strongly linked to Female Infertility (FI) development, but the exact causes are unknown. In this study, a transcriptome analysis of FI was conducted with four carcinogenic risk factors, leading to the identification of differentially expressed genes (DEGs) and the discovery of molecular mechanisms associated with cancers and FI progression. Two hub proteins, VEGFA and PIK3R1, were targeted for therapeutic intervention, and certain phytoestrogenic compounds showed high binding affinity and favorable properties for these proteins. The identified pathways, hub proteins, and phytocompounds could serve as new targets and interventions for accurate diagnosis and treatment of multiple diseases.
Proceedings Paper
Computer Science, Artificial Intelligence
Yuan Wang, Min Cao, Zhenfeng Fan, Silong Peng
Summary: This paper proposes a novel 3D facial landmark detection method, which directly locates the coordinates of landmarks from 3D point cloud with a customized graph convolutional network. The method learns geometric features adaptively with the assistance of constructed 3D heatmaps and further predicts 3D landmarks through a local surface unfolding and registration module.
THIRTY-SIXTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTY-FOURTH CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE / THE TWELVETH SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Wen Qian, Hao Luo, Silong Peng, Fan Wang, Chen Chen, Hao Li
Summary: This paper proposes an Unstructured Feature Decoupling Network (UFDN) to address the problem of misalignment of features caused by pose and viewpoint variances in Vehicle Re-Identification (ReID). UFDN aligns features without the need for additional annotation and introduces a cluster-based decoupling constraint to learn diverse but aligned decoupled features. Experimental results demonstrate that UFDN achieves state-of-the-art performance on popular Vehicle ReID benchmarks with both CNN and Transformer backbones.
COMPUTER VISION - ECCV 2022, PT XIV
(2022)
Proceedings Paper
Acoustics
Shaoyu Zhang, Chen Chen, Xiujuan Zhang, Silong Peng
Summary: Mixup is a popular data augmentation technique, but may face label suppression issue when applied to long-tailed data. To address this, Label-Occurrence-Balanced Mixup is proposed, using class-balanced samplers to generate new data and improve the adaptability of mixup to imbalanced data.
2022 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Chen Chen, Hao Dou, Xiyuan Hu, Silong Peng
Summary: In this paper, a new method based on deep metric counter metric is proposed to improve top rank accuracy by optimizing the occurrence count of correct top-rank matches, and a progressive hard sample mining strategy is introduced for training and performance boosting. Extensive experiments demonstrate that the proposed top-rank counter metric outperforms other loss function based deep metrics and achieves state-of-the-art accuracies.
2020 25TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR)
(2021)
Article
Computer Science, Information Systems
Min Cao, Chen Chen, Hao Dou, Xiyuan Hu, Silong Peng, Arjan Kuijper
Summary: In this paper, a lightweight post-processing person re-identification method is proposed, which determines pairwise measure by computing the relationship between the sample and its counterpart's context, leading to higher accuracy and efficiency.
IEEE TRANSACTIONS ON MULTIMEDIA
(2021)
Article
Chemistry, Analytical
Yujia Ying, Huilin Li
Summary: Enzymes play a crucial role as biological catalysts in accelerating biochemical reactions in living organisms. This study proposes a convenient method for monitoring enzymatic catalytic processes using native top-down mass spectrometry. By exploring the heterogeneity of the chymotrypsin sample and using tandem mass spectrometry, the researchers were able to monitor covalent and noncovalent enzymatic complexes, substrates, and products during catalysis. The results demonstrate that this method has the potential to be a promising tool for characterizing biocatalysts.
ANALYTICA CHIMICA ACTA
(2024)
Article
Chemistry, Analytical
Kang Yang, Shuaibo Shi, Jinyu Wu, Shaolong Han, Shengdi Tai, Shishen Zhang, Kun Zhang
Summary: H2O and D2O are important analogues closely related to various industries and monitoring fields. This study successfully distinguishes and detects H2O and D2O by designing a novel eu(III)-macrocycle with dual emitters, Eu-2a, and conducting fluorescence titration experiments.
ANALYTICA CHIMICA ACTA
(2024)
Article
Chemistry, Analytical
Julia Kuligowski, Alvaro Perez-Rubio, Marta Moreno-Torres, Polina Soluyanova, Judith Perez-Rojas, Ivan Rienda, David Perez-Guaita, Eugenia Pareja, Ramon Trullenque-Juan, Jose Castell, Marcha Verheijen, Florian Caiment, Ramiro Jover, Guillermo Quintas
Summary: This study introduces a novel variable selection approach called cluster PLS (c-PLS) to assess the joint impact of variable groups selected based on biological characteristics on the predictive performance of a multivariate model. The usefulness of c-PLS is shown using miRNomic and metabolomic datasets obtained from the analysis of liver tissue biopsies.
ANALYTICA CHIMICA ACTA
(2024)
Article
Chemistry, Analytical
Meixue Lai, Lijie Zhong, Siyi Liu, Yitian Tang, Tingting Han, Huali Deng, Yu Bao, Yingming Ma, Wei Wang, Li Niu, Shiyu Gan
Summary: This study presents a method for constructing wearable sweat electrolyte sensors using carbon fiber-based solid-contact ion-selective electrodes (SC-ISEs). By using carbon fibers extracted from commercial cloth as electrode material, the cost and reproducibility issues of flexible SC-ISEs were addressed. The results showed that the carbon fiber-based SC-ISEs exhibited reversible voltammetric and stable impedance performances, and had high reproducibility of standard potentials between normal and bending states.
ANALYTICA CHIMICA ACTA
(2024)
Article
Chemistry, Analytical
Ke Yang, Ying Liu, Min Deng, Peipei Wang, Dan Cheng, Songjiao Li, Longwei He
Summary: A near-infrared fluorescent probe has been developed to accurately measure the levels of peroxynitrite (ONOO-) in the endoplasmic reticulum (ER) in acute lung injury (ALI). The probe demonstrated rapid response, high selectivity, good sensitivity, and enhanced fluorescence intensity in response to ONOO-. It was successfully used to detect changes in ONOO- levels and showed significant increases in an ALI cell model and an ALI mouse model.
ANALYTICA CHIMICA ACTA
(2024)
Article
Chemistry, Analytical
Yanping Wang, Yuemei Chen, Kejun Li, Jinrong Zhou, Xin Yuan, Mei Zhang, Ke Huang
Summary: In this work, a portable analytical system based on point discharge chemical vapor generation atomic emission spectrometry (PD-CVG-AES) coupling with gold filament enrichment was designed. The highly sensitive analysis of Hg2+ indirectly realized the detection of ascorbic acid (AA). The measurement is based on the fact that Ag+ can decrease the concentration of Hg2+ by forming Ag-Hg amalgam in the presence of the reductant SnCl2, while AA can pre-reduce Ag+ to Ag0, leading to the generation of silver nanoparticles (Ag NPs). The developed novel analytical strategy broadens the application of microplasma-based AES and offers a higher level of sensitivity compared to current AA detection techniques.
ANALYTICA CHIMICA ACTA
(2024)
Article
Chemistry, Analytical
Yundi Huang, Bo Song, Kaiwen Chen, Deshu Kong, Jingli Yuan
Summary: This study developed two lysosome-targetable background-free TGL probes for efficient and accurate detection of 1O2, which can be used for monitoring endogenous 1O2 concentrations in lysosomes and discriminating variability induced by different photosensitizers. Furthermore, a smart luminescent sensor film was successfully prepared for on-site 1O2 production detection during PDT processes, offering a promising clinical monitoring tool for skin diseases.
ANALYTICA CHIMICA ACTA
(2024)
Article
Chemistry, Analytical
Wei Lang, Jia-Mei Qin, Qian-Yong Cao
Summary: A novel polymer-based probe P1 was successfully synthesized for fluorescently ratiometric sensing of H2S with high selectivity and sensitivity. A smartphone sensing platform was constructed to conduct visual quantitative detection of H2S. P1 can be employed in evaluating the level fluctuations of H2S in living cells, testing water samples/wine samples, and monitoring food freshness.
ANALYTICA CHIMICA ACTA
(2024)
Article
Chemistry, Analytical
Yuanyuan Qin, Shuda Liu, Shuyun Meng, Dong Liu, Tianyan You
Summary: The study developed a split aptamer-based sandwich-type ratiometric biosensor for the detection of 17 beta-estradiol (E2) using photoelectrochemical and electrochemical assays. The biosensor utilized split aptamer fragments to recognize E2 and trigger a hybridization chain reaction, resulting in the production of double-stranded DNA labeled with CdTe quantum dots. This DNA complex was able to sensitize CdTe quantum dots and generate response signals for E2 detection. The developed biosensor demonstrated high sensitivity and accuracy with two linear ranges and low detection limits.
ANALYTICA CHIMICA ACTA
(2024)
Article
Chemistry, Analytical
Siriwan Teepoo, Jongjit Jantra, Khaunnapa Panapong, David Taiwo Ajayi
Summary: A novel immunochromatographic assay based on hyperbranched Au plasmonic blackbodies with a smartphone readout was developed for rapid and sensitive detection of leucomalachite green residues in fish and shrimp products.
ANALYTICA CHIMICA ACTA
(2024)
Article
Chemistry, Analytical
Andrea L. Larraga-Urdaz, Borja Moreira-Alvarez, Jorge Ruiz Encinar, Jose M. Costa-Fernandez, Maria Luisa Fernandez-Sanchez
Summary: A major challenge in the 21st century is the development of point-of-care diagnostic tools. In this study, a highly sensitive and simple bioassay using AuNPs and MNAzymes was developed for rapid detection and quantification of miRNA-4739. The proposed strategy shows potential for breast cancer diagnosis.
ANALYTICA CHIMICA ACTA
(2024)
Article
Chemistry, Analytical
Xiaohan Zhao, Anyu Wang, Lingzi Zhai, Jiuhe Gao, Sizhe Lyu, Yingshan Jiang, Tian Zhong, Ying Xiao, Xi Yu
Summary: A novel method using polystyrene-coated magnetic nanoparticles for extracting monohydroxy polycyclic aromatic hydrocarbons from urine samples was investigated. The proposed method is simple, sensitive, and efficient, with desirable sensitivity for analyzing low-abundance metabolites in large volumes of complex urine samples.
ANALYTICA CHIMICA ACTA
(2024)
Article
Chemistry, Analytical
Ke Quan, Yuqing Zeng, Wenke Zhang, Fengfeng Li, Mengjiao Li, Zhihe Qing, Linlin Wu
Summary: In this study, a visual and reusable biosensor was developed for detecting substrates that are closely associated with human physiological health. The immobilized oxidase showed higher stability and sensitivity under harsh conditions, enabling reliable detection of substrates in complex fluids.
ANALYTICA CHIMICA ACTA
(2024)
Article
Chemistry, Analytical
Dongjuan Wang, Xiuqian Ding, Jinling Xie, Juan Wang, Guanhao Li, Xin Zhou
Summary: In this study, a three-in-one sensor was developed for real-time detection of biogenic amines (BAs) with high sensitivity and selectivity. The sensor showed multimodal responses and could be used to fabricate portable devices for on-site non-destructive assessment of food spoilage indicators.
ANALYTICA CHIMICA ACTA
(2024)
Article
Chemistry, Analytical
Jinting Meng, Zihao Xu, Shasha Zheng, Hongqun Yang, Tianfu Wang, Hong Wang, Yingwei Zhang
Summary: This study demonstrates the development of a cascade signal amplification system using a multi-pedal DNA walker and strand displacement reactions for the electrochemical detection of miRNA-155. The biosensor exhibited high sensitivity, selectivity, and the potential for clinical applications.
ANALYTICA CHIMICA ACTA
(2024)
