Article
Automation & Control Systems
Valeria Fonseca Diaz, Bart De Ketelaere, Ben Aernouts, Wouter Saeys
Summary: This study aims to select the most informative calibration samples in an unsupervised way based on spectral measurements by providing guidelines for addressing challenges in PLSR model building. Recommendations include calculating a sample size exceeding the model complexity by a factor of 12, performing selection in a PCA score space with a sufficient number of principal components, and using methods such as Kennard-Stone.
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
(2021)
Article
Engineering, Chemical
Jing Wu, Lili Tang, Shaoqin Jin, Xuan Li, Huan Liu, Dong Li, Yiqi Liu, Qilin Wang
Summary: An adaptive hybrid soft sensor model with semisupervised learning is proposed to address multirate issues in wastewater treatment processes, using different regression models to predict hard-to-measure variables and achieving better prediction accuracy and shorter time consumption compared to standard models.
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
N. Muruganandam, V. Venkatraman, R. Venkatesan
Summary: This article introduces a technique called MWIRMAB-RAR, which uses a multivariate weighted isotonic regression function to select resource-efficient sensor nodes and establishes multiple route paths to improve data transmission efficiency and reduce energy consumption, packet loss rate, and delay.
Article
Chemistry, Analytical
Fei Cheng, Chunhua Yang, Hongqiu Zhu, Yonggang Li, Lijuan Lan, Kai Wang
Summary: NICEM is a semi-supervised spectral calibration method that decouples spectral features based on information lossless decoupling. It uses the NICE model to learn the sample distribution and evaluates the association between latent feature variables and attributes using the maximum mutual information coefficient. The method is applicable for quantitative analysis of spectral data and has shown promising results in experiments.
ANALYTICAL CHEMISTRY
(2023)
Article
Chemistry, Analytical
Giulia Gorla, Alessandro Taiana, Ricard Boqu, Paolo Bani, Olga Gachiuta, Barbara Giussani
Summary: The use of miniaturized NIR spectrometers is becoming more popular in scientific research, focusing on developing rapid and user-friendly methods following the principles of green analytical chemistry. In this study, statistical strategies were employed to understand the features and limitations of handheld NIR instruments. By evaluating a hygroscopic powder sample, a step-by-step methodology was presented to obtain realistic models with miniaturized NIR spectrometers. The results were compared with a benchtop system for reference.
ANALYTICA CHIMICA ACTA
(2022)
Article
Spectroscopy
Yue Sun, Meng Yuan, Xiaoyan Liu, Mei Su, Linlin Wang, Yingzi Zeng, Hengchang Zang, Lei Nie
Summary: This study proposed a method to construct calibration and validation sets by selecting samples maximally similar to the test samples based on spectra data, which is more suitable and specific for unknown test samples, improving measurement accuracy and predictive performance.
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
(2021)
Article
Automation & Control Systems
Pema Lhamo, Biswanath Mahanty
Summary: This study demonstrates that multiple analytical methods can be used to accurately predict residual biomass in Cupriavidus necator, overcoming the limitations of optical density measurements when cell size and morphology change.
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
(2022)
Article
Chemistry, Multidisciplinary
Maogang Li, Weipeng Lai, Ruirui Li, Jiajun Zhou, Yingzhe Liu, Tao Yu, Tianlong Zhang, Hongsheng Tang, Hua Li
Summary: With the development of green chemistry, the new generation of energetic materials exhibit higher insensitivity, density and energy. An ensemble modeling strategy combining Monte Carlo (MC) and variable importance measurement (VIM) improved random forest (RF) and quantitative structure-property relationship (QSPR) was proposed for accurate prediction of detonation performance of energetic materials, which was successfully applied to density prediction.
Article
Agriculture, Multidisciplinary
Dimitrios S. Kasampalis, Pavlos Tsouvaltzis, Konstantinos Ntouros, Athanasios Gertsis, Ioannis Gitas, Dimitrios Moshou, Anastasios S. Siomos
Summary: The nutritional composition of bell pepper fruits is mainly affected by the ripening stage at harvest, with non-destructive techniques reliably predicting internal quality. Algorithms such as genetic algorithm identified significant regions and wavelengths for assessing nutritional components in peppers.
JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE
(2022)
Article
Endocrinology & Metabolism
Denise M. Selegato, Thamires R. Freitas, Marcos Pivatto, Amanda D. Pivatto, Alan C. Pilon, Ian Castro-Gamboa
Summary: In this study, a comprehensive strategy for metabolic profiling was demonstrated using F. oxysporum as a model system. The results showed that multivariate data analysis can reveal the chemical metabolism information during fungal growth and identify compounds produced in response to alkaloids. Additionally, the study reported the annotation of analogs produced by F. oxysporum as a defense response to toxic plant metabolites.
Article
Chemistry, Analytical
Gloria Rovira, Itziar Ruisanchez, M. Pilar Callao
Summary: This study proposes a standardization strategy for dealing with seasonal variability in the authentication of extra virgin oils from the PDOs Les Garrigues and Siurana. A PLS-DA two-class model was developed and validated using fluorescence spectroscopy measurements. The results show that standardization is a good strategy for extending the usefulness of the models when predicting samples subject to seasonal variability.
MICROCHEMICAL JOURNAL
(2023)
Article
Automation & Control Systems
Wei Chen, Jiusun Zeng, Xiaobin Xu, Shihua Luo, Chuanhou Gao
Summary: This article introduces a fault isolation framework based on structured sparsity modeling, which incorporates process structure information into fault diagnosis methods to achieve more accurate fault isolation.
JOURNAL OF PROCESS CONTROL
(2021)
Article
Mathematical & Computational Biology
Annika Stroemer, Nadja Klein, Christian Staerk, Hannah Klinkhammer, Andreas Mayr
Summary: Within the framework of generalized additive models, we have developed a model-based boosting approach for multivariate distributional regression, which allows for simultaneous modeling of all distribution parameters of a multivariate response conditional on explanatory variables. It is applicable to potentially high-dimensional data and incorporates data-driven variable selection. The approach also enables modeling the association between multiple continuous or discrete outcomes through relevant covariates.
STATISTICS IN MEDICINE
(2023)
Article
Multidisciplinary Sciences
Hua Tan, Shilin Yan, Sirong Zhu, Pin Wen
Summary: This article presents a new method for creep modeling and performance prediction of composite materials. An intelligent computing method is used to derive sub-functions related to temperature, and an improved gene expression programming algorithm is proposed. The validity of the developed model is verified through experiments, and the shift factor is solved using the Arrhenius equation. The creep master curve is derived and evaluated using different models, showing the effectiveness of the improved algorithm.
SCIENTIFIC REPORTS
(2022)
Article
Energy & Fuels
Hanmin Sheng, Xin Liu, Libing Bai, Hanchuan Dong, Yuhua Cheng
Summary: This study proposes a novel weighted Gaussian process regression method for SOH estimation, which reduces the model's dependence on data through knowledge transfer. Experimental results show that the proposed method achieves reliable prediction results.
JOURNAL OF ENERGY STORAGE
(2021)
Article
Chemistry, Analytical
Gang Qu, Yuxin Zhao, Qiaoli Zhang, Jina Wu, Xiaosen Li, Yang Yang, Shilei Liu
Summary: In this study, magnetic mesoporous materials combined with real-time in situ mass spectrometry were used for the high-throughput detection of hydrolyzed products of organophosphorus nerve agents. The method showed good linearity, low limits of detection and quantification, and high extraction recoveries. The magnetic preparation method used was quick, cost-effective, rugged, and safe. The results demonstrated the potential of this method for rapid and efficient determination of the target analytes in environmental samples.
ANALYTICAL METHODS
(2024)
Article
Chemistry, Analytical
Anna Hildebrand, Mariam Merchant, Danny O'Hare
Summary: Substandard and falsified artemisinin derivatives in antimalarials have caused significant deaths and economic losses. This study evaluates the feasibility of voltammetric methods for identifying and quantifying artemether. The findings suggest that electrochemical analysis shows promise as a method for artemether identification and quantification.
ANALYTICAL METHODS
(2024)
Article
Chemistry, Analytical
Marx Osorio Araujo Pereira, Alvaro Ferreira Junior, Edson Silvio Batista Rodrigues, Helena Mulser, Giovanna Nascimento de Mello e Silva, Wallans Torres Pio dos Santos, Eric de Souza Gil
Summary: Brazilian spotted fever (BSF) is a serious and rapidly evolving disease. A new impedimetric immunosensor was developed for rapid diagnosis by measuring specific antibodies in plasma. The sensor demonstrated selectivity and accuracy, and has potential for important applications in diagnostic testing.
ANALYTICAL METHODS
(2024)
Article
Chemistry, Analytical
Kathrin Schilling, Ronald A. Glabonjat, Olgica Balac, Marta Galvez-Fernandez, Arce Domingo-Relloso, Vesna Slavkovich, Jeff Goldsmith, Miranda R. Jones, Tiffany R. Sanchez, Ana Navas-Acien
Summary: Analysis of trace elements in urine is an important tool for assessing exposures, diagnosing nutritional status, and guiding public health and healthcare intervention. This study provides a sensitive method for analyzing 18 elements in urine samples, using only 100 μL. The results show good accuracy and sensitivity of the method.
ANALYTICAL METHODS
(2024)
Article
Chemistry, Analytical
Mengya Li, Shijie Liu, Shiliang Guo, Dong Liang, Miaoyun Li, Yaodi Zhu, Lijun Zhao, Jong-Hoon Lee, Gaiming Zhao, Yangyang Ma, Yanxia Liu
Summary: In this study, a magnetic flow device was developed to purify spores in a culture medium system. The device used magnetic nanoparticles to absorb vegetative cells, separating them from the spores. The achieved purity of the collected spores was over 95%. The study also demonstrated a rapid quantitative detection method using Raman spectroscopy.
ANALYTICAL METHODS
(2024)
Article
Chemistry, Analytical
Wanqiong Liu, Zixuan Wu, Jianwei Peng, Zebin Xu, Yong Liang
Summary: Metal-organic frameworks (MOFs) are effective carriers for molecular imprinting, but their poor dispersibility in aqueous solution is a significant drawback. In this study, we have applied amphiphilic block copolymers and molecularly imprinted technology on MOFs to improve the hydrophilicity of molecularly imprinted fluorescent materials.
ANALYTICAL METHODS
(2024)