Acylcarnitine Profiles in Plasma and Tissues of Hyperglycemic NZO Mice Correlate with Metabolite Changes of Human Diabetes by Anna Weiser, Pieter Giesbertz, Hannelore Daniel, Britta Spanier

“…We observed high concentrations of fatty acid-derived ACs in 11 female mice, high abundance of branched-chain amino acid- (BCAA-) derived ACs in 6 male mice, and slight increases in BCAA-derived ACs in the remaining 6 males. Principal component analysis (PCA) including all ACs and AAs confirmed our hypothesis especially in plasma samples by clustering females, males with high BCAA-derived ACs, and males with slight increases in BCAA-derived ACs. …”
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Analysis of Quality Differences in Radix Dipsaci before and after Processing with Salt Based on Quantitative Control of HPLC Multi-Indicator Components Combined with Chemometrics by Hangsha Wu, Yue Lv, Rui Tang, Mingfang Zhao, Yafei Li, Feiyang Wei, Changyu Li, Weihong Ge, Weifeng Du

“…Then, the chemometric methods such as principal component analysis (PCA) and fisher discriminant analysis (FDA) were used to evaluate the quality of raw and salt-processed RD. …”
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Machine‐Learned HASDM Thermospheric Mass Density Model With Uncertainty Quantification by Richard J. Licata, Piyush M. Mehta, W. Kent Tobiska, S. Huzurbazar

“…We utilize principal component analysis for dimensionality reduction, which creates the coefficients upon which nonlinear machine‐learned (ML) regression models are trained. …”
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Exploring shape diversity and sexual dimorphism in two populations of Nigma conducens through geometric morphometrics by Safa M. El-masry, Tarek G. Ismail, Asmaa N. Mustafa

“…This study employed geometric morphometrics to investigate prosoma shape and size variations between two populations of Nigma conducens spiders and between sexes within each population. Principal Component Analysis (PCA) explored shape variation, while Canonical Variate Analysis (CVA) compared shape differences between populations and sexes. …”
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Citizens of the Global South value urban green space: an example from Iran by Sahel Azizkhani Shadisheh, Kamran Shayesteh, Michael Farmer, Gad Perry

“…The average WTP was $0.93 per person per month, totaling over $6.4 million annually. Principal component analysis identified four key predictors of WTP: economic status, geographic origin, gender, and aesthetic preference. …”
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Posterior AD-Type Pathology: Cognitive Subtypes Emerging from a Cluster Analysis by Antonella Cappa, Nicoletta Ciccarelli, Eleonora Baldonero, Marialuisa Martelli, Maria Caterina Silveri

“…Methods. 23 PCA and 16 DAT patients were studied. By a principal component analysis performed on a wide range of neuropsychological tasks, 15 variables were obtained that loaded onto five main factors (memory, language, perceptual, visuospatial, and calculation) which entered a hierarchical cluster analysis. …”
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Dynamic Metabolic Footprinting Reveals the Key Components of Metabolic Network in Yeast Saccharomyces cerevisiae by Pramote Chumnanpuen, Michael Adsetts Edberg Hansen, Jørn Smedsgaard, Jens Nielsen

“…Using sparse principal component analysis (Sparse PCA), we further identified those pairs of metabolites that significantly contribute to the separation. …”
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Correlates and predictors of homonegativity among Mexican medical students by José Moral de Rubia, Adrián Valle de la O

“…Results: The sample was composed of 202 volunteer participants, who were studying at a private medical school in Monterrey, Mexico. A principal component analysis was performed with scales of assessment that were correlated with HN-16 total score, and yielded three components: masculinity-harshness-externality, religiosity-conservatism, and homosexuality-chivalry-honesty. …”
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Budowa i proporcje ciała warszawskiej młodzieży gimnazjalnej by Joanna Grzelak, Joanna Nieczuja-Dwojacka, Anna Siniarska, Ewa Samul

“…The living conditions were reduced by principal component analysis to three factors (family size, living conditions, environmental stress). …”
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Chemical Differentiation and Quantitative Analysis of Different Types of Panax Genus Stem-Leaf Based on a UPLC-Q-Exactive Orbitrap/MS Combined with Multivariate Statistical Analysi... by Lele Li, Yang Wang, Yang Xiu, Shuying Liu

“…By means of −ESI PRM MS method, the contents of eighteen ginsenosides in Asian ginseng stem-leaf (ASGSL) and American ginseng stem-leaf (AMGSL) were analyzed. The principal component analysis (PCA) model was built to discriminate Asian ginseng stem-leaf (ASGSL) from American ginseng stem-leaf (AMGSL) based on −ESI PRM MS data, and six ginsenosides (F11, Rf, R2, F1, Rb1, and Rb3) were obtained as the markers. …”
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Analysis of Regional Economic Development Differences Based on Intelligent Hybrid Algorithm by Yanyan Li

“…On the basis of summarizing and analyzing previous research works, this paper expounded the research status and significance of regional economic development differences analysis, elaborated the development background, current status, and future challenges of intelligent hybrid algorithms, introduced the methods and principles of principal component distance weighting algorithm and sequential quadratic programming algorithm, constructed a basic model for regional economic development differences based on intelligent hybrid algorithm, conducted the construction of analysis index system and the hybrid of intelligence algorithm, analyzed the regional economic development differences based on intelligent hybrid algorithm, performed the principal component analysis and time-space change analysis of regional economic development, and finally carried out a simulation experiment and its result analysis. …”
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Breaking the Barriers for Women Participation in Agroforestry in the Context of AfCFTA by Patrick Opoku, Awonlimali Kenneth Ali, Peter Ampadu-Daaduam, Dorothy Asare Akoto

“…Exploratory factor analysis involving principal component analysis was used for the data analysis. …”
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Learning model combined with data clustering and dimensionality reduction for short-term electricity load forecasting by Hyun-Jung Bae, Jong-Seong Park, Ji-hyeok Choi, Hyuk-Yoon Kwon

“…Here, we adapt k-means clustering for data clustering, kernel principal component analysis (kernel PCA), universal manifold approximation and projection (UMAP), and t-stochastic nearest neighbor (t-SNE) for dimensionality reduction. …”
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Alterations of Serum Bile Acid Profile in Patients with Crohn’s Disease by Rui Sun, Jingjing Jiang, Ling Yang, Lu Chen, Hong Chen

“…The DCA/(DCA + CA) ratio was also decreased in CD active patients than in CD remission patients while the LCA/(LCA + CDCA) ratio showed no difference between them. Principal component analysis also indicated a clear separation among the three groups, with a total variance of 93.43%. …”
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Credit Risk Assessment of Small and Medium-Sized Enterprises under the Financial Model of Online Supply Chain by Shengli Chen, Dong Wang, Zheng Wan

“…An online supply chain financial credit risk evaluation model for the different industries was then constructed using principal component analysis (PCA) and logistic regression methods. …”
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Financial factors influencing investment willingness in environment-friendly business: Empirical study on an emerging economy by Fairtown Zhou Ayoungman, Md. Shoriful Islam, Mohammad Masukujjaman, Abid Hossain Shawon, Abdullah Al Mahmud

“…The study included 150 corporate executives who are closely involved in investment decisions within their respective organizations. Principal component analysis was used to identify financial influences, and a linear regression model was used to build relationships using SPSS. …”
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Evaluation of the DWT-PCA/SVD Recognition Algorithm on Reconstructed Frontal Face Images by Louis Asiedu, Bernard O. Essah, Samuel Iddi, K. Doku-Amponsah, Felix O. Mettle

“…This study assessed the performance of the principal component analysis and singular value decomposition algorithm using discrete wavelet transform (DWT-PCA/SVD) as preprocessing mechanism on the reconstructed face image database. …”
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Identification of Main Driving Factors of Water Resources Carrying Capacity in Taiyuan City by DING Xiangyi, SHI Xiaolin, WANG Xiangqian, MEI Chao

“…Utilizing the existing evaluation results of the water resources carrying capacity of Taiyuan City,this paper qualitatively analyzed its driving factors of the city,which was based on the analysis of the critical overload/overloading causes of various dimensions including quantity,quality,domain and flow and the consideration of the current situation of water resources in Taiyuan City.The paper also quantitatively identified the driving factors influencing the water resources carrying capacity of Taiyuan City with a combination weighting method of principal component analysis,analytic hierarchy process and entropy weight method.Further,making full use of the respective advantages of qualitative analysis and quantitative identification of driving factors,the paper took the common influencing factors as the main driving factors of the water resources carrying capacity of Taiyuan City.The results indicated that the main driving factors influencing the various dimensions of water resources carrying capacity in the city included the followings:①water quantity dimension:precipitation,per capita water resources,ratio of imported water to consumed water,groundwater extraction coefficient,coefficient of effective utilization of farmland irrigation water,water consumption per 10 000 yuan of industrial added value and wastewater utilization rate;②water quality dimension:water quality compliance rate of water function zone,proportion of water quality inferior to Grade V;③water domain dimension:soil erosion control rate;④water flow dimension:proportion of river ecological water replenishment.The research results can provide references for the plan formulation of improving water resources carrying capacity in Taiyuan City.…”
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PENINGKATAN PERFORMA DETEKSI SERANGAN MENGGUNAKAN METODE PCA DAN RANDOM FOREST by Eko Arip Winanto, Yudi Novianto, Sharipuddin Sharipuddin, Ibnu Sani Wijaya, Pareza Alam Jusia

“…Salah satu karakteristik dari metode Random Forest adalah kemampuannya dalam mengatasi masalah overfitting dan kualitas prediksi yang baik. Principal Component Analysis (PCA) adalah teknik statistik yang digunakan untuk mengurangi dimensi data dengan memproyeksikannya ke ruang fitur yang lebih rendah. …”
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Motion Intention Analysis-Based Coordinated Control for Amputee-Prosthesis Interaction by Fei Wang, Shiguang Wen, Chengdong Wu, Yuzhong Zhang, Jincheng Li

“…By employing principal component analysis, the measured angular velocities were processed and the motion synergy was obtained in the final. …”
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