Assessment of nutritional, antinutritional, antioxidant and functional properties of different soybean varieties: implications for soy milk development by Kehulum Getaneh Zewudie, Habtamu Fekadu Gemede

“…In particular, Gute-19 soybean varieties contained significantly high amounts of crude protein, ash, crude fat, calcium, iron, and zinc. Principal component analysis showed nutritional variability and six independent clusters in varieties; this category was useful for preparing products such as soymilk. …”
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Preliminary Study on the Genetic Structure and Functional Candidate Genes of Grassland-Thoroughbreds Based on Whole-Genome Resequencing by Wenqi Ding, Wendian Gong, Tugeqin Bou, Lin Shi, Yanan Lin, Xiaoyuan Shi, Zheng Li, Huize Wu, Manglai Dugarjaviin, Dongyi Bai, Yiping Zhao

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Tailoring the functional properties of Jir starch from pearl millet: Effects of extraction layer, fermentation time, and sudanese genotypes by Manhal Gobara Hamid, Khitma A. Sir Elkhatim, Amro B. Hassan, Mohamed A Ibraheem, Yousif M.A. Idris, Faraz Muneer, Mohammed Elsafy, Mahbubjon Rahmatov, Eva Johansson, Tilal Abdelhalim

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Phenotypic variability of Smallanthus sonchifolius germplasm of Peru by Angel Esteban Santa Cruz Padilla, Jorge Luis Vásquez Orrillo, Silvia Yanina Rodríguez López, Araceli Eugenio Leiva, Ricardo Manuel Bardales-Lozano, Juan F. Seminario, Hipolito Murga-Orrillo

“…Multiple correspondence analysis and principal component analysis revealed that the variables propagule color, leaf shape, root pulp color, leaf length and width, root weight per plant, and yield contributed significantly to the discrimination and identification of promising accessions. …”
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PCA-FSA-MLR Model and Its Application in Runoff Forecast by GUO Cunwen, CUI Dongwen

“…To improve the accuracy of runoff forecast,and establish a runoff forecast model combining principal component analysis (PCA),future search algorithm (FSA),and multiple linear regression (MLR),this paper reduces the dimensionality of the sample data by PCA,selects 8 standard test functions and simulates and verifies FSA under different dimensional conditions,optimizes MLR constant terms and partial regression coefficients by FSA,proposes a PCA-FSA-MLR runoff forecast model,constructs PCA-LS-MLR,PCA-FSA-SVM,and PCA-SVM models with dimensionality reduction processing by PCA and FSA-MLR,LS-MLR,FSA-SVM,and SVM without dimensionality reduction processing as a comparison model,and verifies each model through forecasting the annual runoff and monthly runoff in December of Longtan station in Yunnan Province.The results show that:①FSA has better optimization accuracy and global extremum search ability under different dimensional conditions;②The average absolute relative error of the annual runoff and monthly runoff in December of Longtan station through PCA-FSA-MLR model are 1.63% and 3.91% respectively,and its forecast accuracy is better than the other 7 models,with higher forecast accuracy and stronger generalization ability;③For the same model,the forecast accuracy after dimensionality reduction processing by PCA is better than that without dimensionality reduction processing,so the data dimensionality reduction by PCA is helpful to improve the forecast accuracy of models.…”
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Hand dexterity and mobility independently predict cognition in older adults: a multi-domain regression analysis by Thomas Rudolf Schneider, Ansgar Felbecker, Ansgar Felbecker, Ben von Mitzlaff, Ben von Mitzlaff, Gregor Weissofner, Gregor Weissofner, Sarah Meier, Sarah Meier, Patrick Eggenberger, Patrick Eggenberger, Patrick Eggenberger, Simon Annaheim

“…From a neuropsychological battery, a primary Global Cognitive Composite score (GCCS) and three secondary domain scores were derived using Principal Component Analysis (PCA). Motor predictors included the Nine-Hole Peg Test (NHPT), grip strength, Apraxia Screen of TULIA (AST), SPPB sub-tests (5-chair-rises time (5CRT), 4 m-walk time (4MWT), balance), and inertial measurement unit (IMU)-based gait parameters. …”
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Enhancing Smart City Functions through the Mitigation of Electricity Theft in Smart Grids: A Stacked Ensemble Method by Muhammad Hashim, Laiq Khan, Nadeem Javaid, Zahid Ullah, Ifra Shaheen

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Function of 18F-FDG PET/CT radiomics in the detection of checkpoint inhibitor-induced liver injury (CHILI) by Clémence M. C. Huigen, Alexander Coukos, Sofiya Latifyan, Marie Nicod Lalonde, Niklaus Schaefer, Daniel Abler, Adrien Depeursinge, John O. Prior, Montserrat Fraga, Mario Jreige

“…The patients’ liver and spleen were contoured on the anonymized PET/CT imaging data, followed by radiomics feature extraction. Principal component analysis (PCA) and Bonferroni corrections were used for statistical analysis and exploration of radiomics features related to CHILI. …”
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A Comparative Study of the Structural, Morphological, and Functional Properties of Native Potato Starch and Spray-Dried Potato Starch by Anna Marinopoulou, Maria Zoumaki, Dimitrios Sampanis, Vassilis Karageorgiou, Stylianos Raphaelides, Athanasios Goulas

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Dual-functionality of Nocardiopsis alba B57 in biocontrol and plant growth: a metabolomic approach to agricultural sustainability by Osama Abdalla Abdelshafy Mohamad, Yong-Hong Liu, Tamer Elsamahy, Shuai Li, Rajivgandhi Govindan, Nigora Kuchkarova, Shaimaa Hatab, Yuanming Zhang, Wen-Jun Li

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Elevational adaptation and distribution of woody saplings in a mountain forest: Insights from functional traits and mycorrhizal associations by Zuhua Wang, Xia Cai, Min Liu, Haibo Li, Jiayan Jiang, Jugang Wang, Fagen Qiu

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Deep Learning- and Multi-Point Analysis-Based Systematic Deformation Warning for Arch Dams by Tao Zhou, Xiubo Niu, Ning Ma, Futing Sun, Shilin Gong

“…Secondly, combining this with principal component analysis, a systematic deformation residual index with multiple points is established. …”
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Validation of the Chinese version of Brief Assessment of Cognition in Schizophrenia by Wang LJ, Lin PY, Lee Y, Huang YC, Hsu ST, Hung CF, Chen CK, Chen YC, Wang YL, Tsai MC

“…Results: The BACS had good test–retest reliability, and all BACS subtests had statistically insignificant practice effects. Principal components analysis demonstrated that a one-factor solution best fits our dataset (60.9% of the variance). …”
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Interdisciplinary framework for cyber-attacks and anomaly detection in industrial control systems using deep learning by Qawsar Gulzar, Khurram Mustafa

“…Several feature selection techniques exclude features that fail to match the specified criteria. We employed Sparse Principal Component Analysis (SPCA) to extract higher-order features. …”
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Gut Microbiome Diversity and Uric Acid in Serum and Urine by Cecilie Ness, Dmitri Svistounov, Marit D. Solbu, Natalia Petrenya, Neoma Boardman, Kirsti Ytrehus, Trond G. Jenssen, Andrew Holmes, Stephen J. Simpson, Svetlana N. Zykova

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Quantitative Investigation of Hand Grasp Functionality: Thumb Grasping Behavior Adapting to Different Object Shapes, Sizes, and Relative Positions by Yuan Liu, Bo Zeng, Li Jiang, Hong Liu, Dong Ming

“…When the Y deviation changing from proximal to distal, thumb opposition rotation (Rot) and flexion (IP and MCP joint) angles were increased and decreased, respectively. For principal component analysis (PCA) results, thumb grasp behavior can be accurately reconstructed by first two principal components (PCs) which variance explanation ratio reached 93.8% and described by the inverse and homodromous coordination movement between thumb opposition and IP flexion. …”
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The emerging role of mitochondria in the pharmacological and toxicological effects of Tripterygium wilfordii Hook F: functions, targets and new therapeutic applications by Zhonghao Liu, Dan Li, Xiongwen Yang, Xisha Chen, Chengxiao Fu

“…Through a systematic analysis of current literature, this review deciphers the dual regulatory role of mitochondrial function in mediating both therapeutic efficacy and adverse effects of TWHF-derived active compounds. …”
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Thriving in golden years: Promoting psychological well-being for healthy ageing in India by Dhananjay W Bansod, Raghunath Mandi

“…Methods: We created composite score of healthy ageing using Principal Component Analysis based on LASI (wave-1) data 2017–18 in accordance with the WHO framework of healthy ageing based on the functional ability of an individual. …”
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Variation in plant functional traits explains the substitution distribution and allocation strategy of Stipa species across natural grasslands of Ningxia, Northern China by Jun Yang, Xiaowei Li, Junlong Yang, Shuang Yu, Hongmei Zhang, Bo Yang

“…Then, on the species substitution gradient, principal component analysis (PCA) was used to verify and quantify the leaf economic spectrum (LES), root economic spectrum (RES), and whole‐plant economic spectrum (WPES), with the relation between these spectra investigated by fitting standardized major axis regressions. …”
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Correlation study of BDNF/TrkB/CREB, violence, and cognitive function in first-episode drug-naive schizophrenia patients by Tiankai Jiang, Zhipeng Li, Tao Yu, Xudong Zhou, Tiantian Jiang, Yuhang Liang, Chen Yu, Min Zhu, Wenyu Wu

“…Multivariate linear regression suggested CREB plays a crucial role in both violent behavior and cognitive function in SCZ patients. Principal component analysis (PCA) combined highly correlated P_score, N_score, and PANSS_total into one principal component PC1, with logistic regression identifying PC1 as an associated factor for violence. …”
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