Journal of Chemometrics最新文献

{"title":"Fault Detection Strategy of Partial Least Squares Based on Temporal Neighborhood Difference","authors":"Liwei Feng,&nbsp;Shaofeng Guo,&nbsp;Yifei Wu,&nbsp;Yu Xing,&nbsp;Yuan Li","doi":"10.1002/cem.3621","DOIUrl":"https://doi.org/10.1002/cem.3621","url":null,"abstract":"<div>\u0000 \u0000 <p>Aiming at the difficulty of detecting time-lag faults in dynamic processes, a fault detection strategy based on time neighborhood difference (TND) is proposed, and it is introduced into the partial least squares (PLS) method to suggest the PLS-TND fault detection method. The TND method takes the mean to the multibatch training set to obtain a baseline training set, and it constructs the mean squared Euclidean distance (MSED) statistic by calculating the average distance between the sample's first <i>k</i>-moments neighborhood samples and samples at the same moment in the baseline training set. The TND method can help the PLS method to effectively detect time-lag faults and significantly improve the fault detection capability of PLS by measuring the overall positional difference between the temporal neighborhood sample set of the sample and its temporal neighborhood sample set in the baseline training set. The PLS-TND method is compared with some classical fault detection methods through a numerical simulation process and a Continuous Stirred Tank Reactor (CSTR) system design fault detection experiment. The PLS-TND method gives the best performance of fault detection.</p>\u0000 </div>","PeriodicalId":15274,"journal":{"name":"Journal of Chemometrics","volume":"38 12","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142860386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dynamic Multiblock Regression for Process Modelling","authors":"Marco Cattaldo,&nbsp;Alberto Ferrer,&nbsp;Ingrid Måge","doi":"10.1002/cem.3618","DOIUrl":"https://doi.org/10.1002/cem.3618","url":null,"abstract":"<p>The study introduces three novel strategies for incorporating capabilities for dynamic modelling into multiblock regression methods by integrating sequentially orthogonalised partial least squares (SO-PLS) with different dynamic modelling techniques. The study evaluates these strategies using synthetic datasets and an industrial example, comparing their performance in predictive ability, identification of process dynamics, and quantification of block contributions. Results suggest that these approaches can effectively model the dynamics with performance comparable to state-of-the-art methods, providing, at the same time, insight into the dynamic order and block contributions. One of the strategies, sequentially orthogonalised dynamic augmented (SODA)–PLS, shows promise by ensuring that redundant information in the time dimension is not included, resulting in simpler and more easily interpretable dynamic models. These multiblock dynamic regression strategies have potential applications for improved process understanding in industrial settings, especially where multiple data sources and inherent time dynamics are present.</p>","PeriodicalId":15274,"journal":{"name":"Journal of Chemometrics","volume":"38 12","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cem.3618","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142860169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SFMD-X: A New Functional Data Classifier Based on Shrinkage Functional Mahalanobis Distance","authors":"Shunke Bao,&nbsp;Jiakun Guo,&nbsp;Zhouping Li","doi":"10.1002/cem.3615","DOIUrl":"https://doi.org/10.1002/cem.3615","url":null,"abstract":"<div>\u0000 \u0000 <p>In this article, we propose a novel classification approach for functional data based on a shrinkage estimate of functional Mahalanobis distance. We first introduce a new shrinkage functional Mahalanobis distance (SFMD), by using this new distance, we transform the functional observations into a set of vector-valued pseudo-samples. Furthermore, we adopt some good classification algorithms designed for multivariate data to this pseudo-samples instead of the original functional data. The new approach has advantage of highly flexible and scalable, that is, it can easily combine with any classification algorithm, such as support vector machine, tree-based methods, and neural networks. We demonstrate the performance of the proposed functional classifier through both extensive simulation studies and two real data applications.</p>\u0000 </div>","PeriodicalId":15274,"journal":{"name":"Journal of Chemometrics","volume":"38 12","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142860168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Practical Framework Integrating Two-Way Chemometric Methods With Three-Way Ones for the Analysis of Hyphenated Chromatographic Data of Complex Systems","authors":"Zhang-Feng Tang,&nbsp;Wei-Wei Wei,&nbsp;Zhi-Guo Wang,&nbsp;Wen Du,&nbsp;Zeng-Ping Chen","doi":"10.1002/cem.3625","DOIUrl":"https://doi.org/10.1002/cem.3625","url":null,"abstract":"<div>\u0000 \u0000 <p>Hyphenated chromatographic techniques are widely used to analyze and characterize complex samples. Chemometric methods are generally needed to extract the qualitative and quantitative information of the target analytes from complex hyphenated chromatographic data. However, neither two-way nor three-way chemometric methods are efficient enough in analyzing hyphenated chromatographic data with both severe peak overlapping and retention time shift across samples. To address this issue, a practical framework was proposed herein. It consists of three chemometric algorithms, that is, (1) “fix-sized moving window evolving target spectral projection” for locating the possible peak positions of the target analytes, (2) “target identification based on singular value comparison” for determining whether the identified peaks are indeed the chromatographic peaks of the target analytes, and (3) “fix-sized moving window evolving trilinear decomposition” for obtaining the quantitative results of the target analytes. Experimental results on the GC-MS data sets of mixture samples of 10 compounds verified that the proposed framework could deal with the problems of both severe peak overlapping and retention time shift across samples. The proposed framework has the advantages of simplicity in concept, easy implementation, and good performance and hence is expected to be a competitive alternative to existing methods for the analysis of hyphenated chromatographic data of complex samples.</p>\u0000 </div>","PeriodicalId":15274,"journal":{"name":"Journal of Chemometrics","volume":"38 12","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142860093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On the Properties of PLS for Analyzing Two-Level Factorial Experimental Designs","authors":"Joan Borràs-Ferrís,&nbsp;Abel Folch-Fortuny,&nbsp;Alberto Ferrer","doi":"10.1002/cem.3620","DOIUrl":"https://doi.org/10.1002/cem.3620","url":null,"abstract":"<p>We present here a novel methodology to analyze data from two-level factorial experimental designs, with or without missing runs, with just one method: partial least squares regression with one response variable (PLS1, hereinafter PLS). This property is very attractive for practitioners because, to the best of our knowledge, no other statistical tool has comparable versatility. In the case of a full and fractional factorial design, the one-PLS component model yields the same analytical solution as multiple linear regression (MLR), not only in the estimation of the effects but also in their statistical significance. When having missing runs in the factorial design, PLS is of particular interest as it is a powerful tool when dealing with complex correlation structures, as opposed to MLR. Thus, we challenge the widely held view that PLS is useful only when dealing with nonexperimental design (i.e., correlated observational data). The methodology is illustrated by two illustrative examples and synthesized by an easy-to-follow route map useful for practitioners.</p>","PeriodicalId":15274,"journal":{"name":"Journal of Chemometrics","volume":"38 12","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cem.3620","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142862128","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"3D Fluorescence Spectroscopy Combined With Chemometrics as a Tool for Control of Imprinted Protein Purification From Template Molecules","authors":"Natalia A. Burmistrova,&nbsp;Polina M. Ilicheva,&nbsp;Kirill Yu. Presnyakov,&nbsp;Pavel S. Pidenko,&nbsp;Douglas N. Rutledge","doi":"10.1002/cem.3622","DOIUrl":"https://doi.org/10.1002/cem.3622","url":null,"abstract":"<div>\u0000 \u0000 <p>Imprinted proteins (IPs) are promising alternatives to natural recognition systems, such as biological receptors or antibodies. One of the crucial stages during development of IPs is removal of the template molecules from its complex with the protein. In this study, bovine serum albumin was imprinted in the presence of 4-hydroxycoumarin (4-HC); purification of IPs were carried out by dialysis, and fluorescence 3D spectroscopy was used to monitor the IP purification process. Excitation–emission matrix (EEM) was further investigated via several chemometric algorithms (principal component analysis [PCA], parallel factor analysis [PARAFAC], and independent components analysis [ICA]). We found that the models using PARAFAC and ICA worked better than those of PCA. It was shown that PARAFAC and ICA analyses allow not only to recognize IP sample with signal close to nonimprinted protein, but also to provide recommendations on the optimal dialysis time.</p>\u0000 </div>","PeriodicalId":15274,"journal":{"name":"Journal of Chemometrics","volume":"38 12","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142862246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On the Replicability of the Thermodynamic Modeling of Spectroscopic Titration Data in the Nickel(II) En System","authors":"Fenton C. Lawler,&nbsp;Ryan S. Storteboom,&nbsp;Plinio D. Rosales-Lopez,&nbsp;Madison N. Hoogstra,&nbsp;Katherine J. Selvaggio,&nbsp;Trevina Chen,&nbsp;Krista A. Zogg,&nbsp;Dafna L. Heule,&nbsp;Noah J. Pehrson,&nbsp;Aerin E. Baker,&nbsp;Douglas A. Vander Griend","doi":"10.1002/cem.3619","DOIUrl":"https://doi.org/10.1002/cem.3619","url":null,"abstract":"<div>\u0000 \u0000 <p>Characterizing complicated solution phase systems in situ requires advanced modeling techniques to capture the intricate balances between the many chemical species. Due to the error inherent in any scientific measurement, a spectrophotometric titration experiment with nickel(II) and ethylenediamine (en) was repeated six times using an autotitrator to test the replicability of the data and the consistency of the resulting thermodynamic model. All six datasets could be modeled very tightly (<i>R</i>² &gt; 99.9999%) with the following eight complexes: [Ni]²⁺, [Ni₂en]⁴⁺, [Nien]²⁺, [Ni₂en₃]⁴⁺, [Nien₂]²⁺, [Ni₂en₅]⁴⁺, [Nien₃]²⁺, and [Nien₆]²⁺. The logK values for the stepwise associative reactions agree with existing literature values for the majority species ([Nien_{n = 1–3}]²⁺) and matched expectations for the minority species; 95% confidence intervals for each logK value were determined via bootstrapping, which quantifies the variability in the binding constant value that is supported by a given dataset. The repeated experiments, which could not be successfully concatenated together, demonstrate that replication is crucial to capturing all the variability in the logK values. Conversely, bootstrapped confidence intervals across multiple experiments can be readily combined to generate an appropriate range for an experimentally determined binding constant.</p>\u0000 </div>","PeriodicalId":15274,"journal":{"name":"Journal of Chemometrics","volume":"38 12","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142861954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analytical Figures of Merit in Univariate, Multivariate, and Multiway Calibration: What Have We Learned? What Do We Still Need to Learn?","authors":"Alejandro C. Olivieri","doi":"10.1002/cem.3613","DOIUrl":"https://doi.org/10.1002/cem.3613","url":null,"abstract":"<div>\u0000 \u0000 <p>An overview of the status of the research in analytical figures of merit is provided, including all calibration scenarios from univariate to multivariate and multiway analytical protocols. Both linear and nonlinear multivariate models are considered. Starting with the simplest multivariate model, inverse least-squares regression, the basic concepts of sensitivity, sample leverage, and limit of detection are introduced. The extension to other multivariate models is discussed, as well as to nonlinear models based on radial basis functions, kernel partial least-squares, and multilayer feed-forward artificial neural networks. Finally, multiway calibration models are discussed, including multilinear decomposition models such as parallel factor analysis (PARAFAC) and multivariate curve resolution–alternating least-squares (MCR-ALS). In the latter case, recent developments concerning the pervasive phenomenon of rotational ambiguity are discussed. Unfinished works and areas where further research efforts are needed to develop closed-form expressions and to fully understand their meaning are included.</p>\u0000 </div>","PeriodicalId":15274,"journal":{"name":"Journal of Chemometrics","volume":"38 11","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142666077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On Hidden Rank Deficiency in MCR Problems","authors":"Tomass Andersons,&nbsp;Mathias Sawall,&nbsp;Martina Beese,&nbsp;Christoph Kubis,&nbsp;Klaus Neymeyr","doi":"10.1002/cem.3608","DOIUrl":"https://doi.org/10.1002/cem.3608","url":null,"abstract":"<p>Pure component decomposition problems in chemometrics can be classified into rank-regular and rank-deficient problems. Rank-deficient problems are characterized by a spectral data matrix that has a lower rank than the number of chemical species. However, it is possible that there exists rank-regular factorization of the spectral data matrix, but none of these solutions can be interpreted chemically, and only a solution of the MCR problem with rank deficiency is chemically meaningful. Then we say that the underlying problem suffers from a hidden rank deficiency. In this paper, MCR problems with hidden rank deficiency are introduced and analyzed with several examples for problems of rank 2 and rank 3. The area of feasible solutions is determined with the help of additional constraints on the solution.</p>","PeriodicalId":15274,"journal":{"name":"Journal of Chemometrics","volume":"38 12","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cem.3608","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142861953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Paul Geladi (1951–2024) Chemometrician, spectroscopist and pioneer","authors":"Beatriz Galindo-Prieto,&nbsp;Johan Linderholm,&nbsp;Hans Grahn","doi":"10.1002/cem.3614","DOIUrl":"https://doi.org/10.1002/cem.3614","url":null,"abstract":"&lt;p&gt;Prof. Paul Geladi was born the 30&lt;sup&gt;th&lt;/sup&gt; of June of 1951 in Schoten (Belgium) and passed away peacefully on the 18&lt;sup&gt;th&lt;/sup&gt; of May of 2024 in Umeå (Sweden).&lt;/p&gt;&lt;p&gt;Paul Geladi was a brilliant chemometrician and professor specialized in multivariate data analysis (especially, partial least squares methods), multivariate image analysis, multiway analysis, and spectroscopy (near-infrared), as well as a kind and emphatic person with colleagues, students, friends and family. His work trajectory includes, among other, a list of more than 190 publications (with &gt;29,000 citations) that shows the extent and vigour of Paul, both in life and work.&lt;/p&gt;&lt;p&gt;Paul's passion for nature and chemistry awoke in his early years in Schoten, when he was still a very young child, while playing outdoors or experimenting in the attic for hours with the “Chemistry for Beginners” kit that his parents gave him. This was likely the start of a life dedicated to science and research.&lt;/p&gt;&lt;p&gt;After attending Sint-Eduardus in the Londenstraat (Belgium), Paul received his B.Sc. in Chemistry (1974) and his Ph.D. (doctoral degree) in Analytical Chemistry from the University of Antwerp (1979). Afterwards, in the early 1980's, Paul worked in Norway at the non-profit foundation Norwegian Computing Centre, specializing in applied statistics, and accepted a position as Associate Professor in Chemometrics at the Department of Chemistry of Umeå University (Sweden), generating his most cited publication, the tutorial &lt;i&gt;Principal Component Analysis&lt;/i&gt; (Wold, Esbensen &amp; Geladi, 1987). Paul also worked as a visiting Professor at the Department of Chemistry, University of Washington, Seattle, where he wrote his second most cited publication, &lt;i&gt;Partial least-squares regression: a tutorial&lt;/i&gt; (Geladi &amp; Kowalski, 1986). In addition, he also held a position as Associate Professor in Chemometrics and Near Infrared Spectroscopy at the University of Vaasa (Finland) since 2003.&lt;/p&gt;&lt;p&gt;In 2007, Paul was appointed Professor of Chemometrics at the Swedish University of Agricultural Sciences (SLU, Umeå, Sweden), which would be his main institution until his retirement in 2016, when he would become Emeritus Professor at SLU. During the active years, Paul was awarded the title of &lt;i&gt;Honorary Doctor of Technology&lt;/i&gt; by the University of Vaasa (Finland, 2011) in recognition of his esteemed scholarship on Near Infrared Spectroscopy and the international impact of his work. Paul was also External Professor at the Department of Food Science of Stellenbosch University (South Africa) between 2011 and 2014. His work and publications on NIR spectroscopy, multivariate data analysis, hyperspectral imaging, chemometric method development, and their applications in a variety of fields, had a tremendous impact in the scientific community, yielding to numerous invitations to present his work in international conferences and meetings.&lt;/p&gt;&lt;p&gt;His outstanding work related to chemometrics, multivariate c","PeriodicalId":15274,"journal":{"name":"Journal of Chemometrics","volume":"38 11","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cem.3614","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142665736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}