Article
Health Care Sciences & Services
Ching-Nung Wu, Sheng-Dean Luo, Shu-Fang Chen, Chi-Wei Huang, Pi-Ling Chiang, Chung-Feng Hwang, Chao-Hui Yang, Chun-Hsien Ho, Wei-De Cheng, Chung-Ying Lin, Yi-Lu Li
Summary: This study analyzed 103 patients with vertigo symptoms who underwent oculomotor tests and brain MRI. The study found that age over 60 and multiple comorbidities were significant factors contributing to discordant interpretation between oculomotor tests and brain MRI. Positive neurological symptoms and higher oculomotor index were significant predictors of central vestibular disorder in patients with vertigo. Caution is needed when interpreting the oculomotor test results in older patients and those with multiple comorbidities.
JOURNAL OF PERSONALIZED MEDICINE
(2022)
Article
Biochemical Research Methods
Kuangnan Fang, Rui Ren, Qingzhao Zhang, Shuangge Ma
Summary: Dimension reduction techniques like PCA, PLS, and CCA are extensively used in the analysis of high-dimensional omics data. Integrative analysis, which outperforms meta-analysis and individual-data analysis, has been developed for multiple datasets with compatible designs. We developed the R package iSFun to facilitate integrative dimension reduction analysis, offering comprehensive analysis options under different models and penalties.
Article
Computer Science, Artificial Intelligence
Pei Li, Wenlin Zhang, Chengjun Lu, Rui Zhang, Xuelong Li
Summary: A novel robust kernel principal component analysis method with optimal mean (RKPCA-OM) is proposed to enhance the robustness of KPCA by automatically eliminating the optimal mean. The theoretical proof guarantees the convergence of the algorithm and the obtained optimal subspaces and means. Exhaustive experimental results validate the superiority of the proposed method.
Article
Engineering, Civil
Honghua Liu, Jing Yang, Ming Ye, Scott C. James, Zhonghua Tang, Jie Dong, Tongju Xing
Summary: This study introduced t-SNE as a graphic approach to assist cluster analysis for groundwater geochemistry data. Compared to PCA, t-SNE performed better in assisting cluster analysis, showing promise as a tool for determining cluster numbers and delineating spatial zones.
JOURNAL OF HYDROLOGY
(2021)
Article
Engineering, Chemical
Abdalhamid Rahoma, Syed Imtiaz, Salim Ahmed
Summary: Sparse principal component analysis (SPCA) provides a sparse description of the loading matrix. This article proposes two methods to calculate confidence intervals of the loading values, which outperform traditional PCA and benchmark SPCA methods in fault detection and diagnosis.
CHEMICAL ENGINEERING SCIENCE
(2021)
Article
Chemistry, Analytical
Michaela Tesarova, Tereza Bouskova, Pavel Cejnar, Jiri Santrucek, Lenka Peterkova, Zdenek Fik, Petra Sazelova, Vaclav Kasicka, Radovan Hynek
Summary: Vestibular schwannoma is the most common benign neoplasm of the cerebellopontine angle. This study demonstrates the potential of in-sample protein digestion combined with LC-MS/MS analysis for fast and routine characterization of vestibular schwannoma at the molecular level.
JOURNAL OF SEPARATION SCIENCE
(2023)
Article
Multidisciplinary Sciences
Makoto Mizuno, Hideaki Aoyama, Yoshi Fujiwara
Summary: This study introduces a novel method called complex Hilbert principal component analysis (CHPCA) and constructs a synchronization network using Hodge decomposition, which enables the extraction of significant comovements with a time lead/delay in high-dimensional data and identification of the time-structure of correlations. Applied to Japanese beer market data, this method reveals co-movements across multiple products in the consumer choice process and uncovers remarkable customer heterogeneity.
Article
Biochemical Research Methods
Charles C. David, Chris S. Avery, Donald J. Jacobs
Summary: JEDi software is an upgraded tool that employs multithreading and user-friendly interface for rapid investigation of conformational motions of biopolymers, including multiple chain proteins. It offers options for Cartesian-based coordinates (cPCA) and internal distance pair coordinates (dpPCA) to construct covariance, correlation, and partial correlation matrices.
BMC BIOINFORMATICS
(2021)
Article
Biochemical Research Methods
Rola Houhou, Petra Rosch, Jurgen Popp, Thomas Bocklitz
Summary: In this study, Raman spectral data were analyzed using B-spline basis functions for approximation, followed by functional principal component analysis and linear discriminant analysis (FPCA-LDA) compared to classical PCA-LDA. Results showed that FPCA-LDA had higher mean sensitivities than PCA-LDA, especially with low signal-to-noise ratio and small peak shifts. However, both methods performed equally with higher signal-to-noise ratio, and a slight improvement was observed when FPCA-LDA was applied to experimental Raman data.
ANALYTICAL AND BIOANALYTICAL CHEMISTRY
(2021)
Article
Materials Science, Characterization & Testing
Nitin Nagesh Kulkarni, Shweta Dabetwar, Jason Benoit, Tzuyang Yu, Alessandro Sabato
Summary: This study improves the accuracy of infrared thermography (IRT) in detecting voids underneath roadways by comparing and validating three advanced image-processing techniques. Among them, sparse principal component thermography (S-PCT) allows determining the physical size of voids with an accuracy above 95%. This research provides a foundation for advancing the use of IRT as a more accurate and cost-effective method for road condition monitoring.
NDT & E INTERNATIONAL
(2022)
Article
Plant Sciences
Csaba Bojtor, Seyed Mohammad Nasir Mousavi, Arpad Illes, Farid Golzardi, Adrienn Szeles, Atala Szabo, Janos Nagy, Csaba L. Marton
Summary: This study aimed to investigate the nutrient acquisition and partitioning of maize and the effects of different nitrogen supplies on its growth and yield. The results showed that NPK application increased the dry matter content of maize, while nitrogen application had no significant effect on this trait. Furthermore, nitrogen application was positively correlated with protein content. It is recommended to use 120 kg/ha of NPK fertilizer for maize cultivation to achieve maximum yield and quality.
Article
Computer Science, Artificial Intelligence
Yunlong Gao, Tingting Lin, Jinyan Pan, Feiping Nie, Youwei Xie
Summary: This paper proposes a new technique called Fuzzy Sparse Deviation Regularized Robust Principal Component Analysis (FSD-PCA) to improve the robustness of Principal Component Analysis (PCA) to noise samples. By introducing sparse deviation and fuzzy weighting, FSD-PCA is able to process noise and principal components separately, thus enhancing its ability to retain principal component information.
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2022)
Article
Chemistry, Physical
E. R. Beyerle, M. G. Guenza
Summary: This study connects PCA to a Langevin model of protein dynamics and analyzes the contributions of energy barriers and hydrodynamic interactions to slow PCA modes of motion. By introducing the LE4PD-XYZ model, which accurately describes anisotropic fluctuations in protein motion, it is found that inclusion of free-energy barriers and hydrodynamic interactions has significant effects on the identification and timescales of slow modes of the protein ubiquitin.
JOURNAL OF CHEMICAL PHYSICS
(2021)
Article
Engineering, Industrial
Arthur Henrique de Andrade Melani, Miguel Angelo de Carvalho Michalski, Renan Favarao da Silva, Gilberto Francisco Martha de Souza
Summary: Through Condition-Based Maintenance strategy, a hybrid framework based on Moving Window Principal Component Analysis (MWPCA) and Bayesian Network (BN) was proposed for automated Fault Detection and Diagnosis (FDD) in machinery. The framework was able to detect and diagnose several simulated failures in a simplified model of a hydrogenerator.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Chemistry, Medicinal
Jingyu Zhang, Jinxin Che, Xiaomin Luo, Mingfei Wu, Weijuan Kan, Yuheng Jin, Hanlin Wang, Ao Pang, Cong Li, Wenhai Huang, Shenxin Zeng, Weihao Zhuang, Yizhe Wu, Yongjin Xu, Yubo Zhou, Jia Li, Xiaowu Dong
Summary: In this study, dimensionality reduction analysis and model molecule validation were used to identify key structural features for improving the oral absorption of BTK-PROTACs. The newly discovered BTK-PROTACs B1 and B2 were optimized based on the results. Compound C13 with improved oral bioavailability, high BTK degradation activity, and selectivity was discovered. It showed inhibitory effects against hematologic cancer cells and attenuated the BTK-related signaling pathway. The oral administration of C13 effectively reduced BTK protein levels and suppressed tumor growth. This study led to the discovery of a new orally bioavailable BTKPROTAC for the treatment of lymphoma.
JOURNAL OF MEDICINAL CHEMISTRY
(2022)