NIRS as an alternative method for table grapes Seedlessness sorting by Chaorai Kanchanomai, Parichat Theanjumpol, Phonkrit Maniwara, Sila Kittiwachana, Sujitra Funsueb, Shintaroh Ohashi, Daruni Naphrom

“…. • The NIR spectral data were analyzed using principal component analysis (PCA). In addition, supervised self-organizing map (SSOM) and quadratic discriminant analysis (QDA) were applied to classify the seedlessness. • The PCA results represented a negative tendency to classify the seedlessness. …”
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Seaweed and yeast extracts as sustainable phytostimulant to boost secondary metabolism of apricot fruits by Noemi Gatti, Moez Maghrebi, Graziella Serio, Carla Gentile, Victor V. Bunea, Ivano Vigliante, Camille Boitte, Christian Garabello, Valeria Contartese, Cinzia M. Bertea, Giuseppe Mannino

“…These metabolic enhancements translated into significantly increased total antioxidant activity, particularly evident in the peel samples. Principal Component Analysis (PCA) revealed distinct effects of the 5.0 and 4.0 L/ha treatments, distinguishing them from lower doses and the control group. …”
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Enhancing physicochemical, bioactive, and nutritional properties of sweet potatoes: Ultrasonic contact drying with slot jet nozzles compared to hot-air drying and freeze drying by Gulcin Yildiz, Yuan Gao, Junzhou Ding, Si Zhu, Guibing Chen, Hao Feng

“…Additionally, FTIR analysis revealed that peaks in specific spectral regions indicated superior preservation of bioactive compounds in SJR + US samples compared to other methods, which was also confirmed by principal component analysis (PCA) and heatmap visualization. …”
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Systematic analysis of co-expression network and gene expression profile of differentially expressed lncRNA-mRNA one week after spinal cord injury by Yi Kang, Yijie Song, Zhongju Shi, Qiang Li, Yigang Lv, Mengfan Hou, Cui Ding, Jing Xie, Yongfu Lou, Chi Zhang, Huan Jian, Xueying Li, Hengxing Zhou, Shiqing Feng

“…Abbreviations: SCI: spinal cord injury; CNS: central nervous system; YLDs: years of life lived with disability; lncRNAs: long noncoding RNAs; mRNAs: messenger RNAs; DE: differentially expressed; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; GSEA: gene set enrichment analysis; RIN: Renewable Identification Number; PCA: principal component analysis; PPI: protein–protein interaction; MF, molecular function; BP: biological process; CC: cellular component; MCODE: molecular complex detection…”
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Design and Dynamic Analysis of Ideological and Political Education Platform Based on Network Multimedia Technology by Xiaowen Chen

“…Because of the thought-political education platform design and ideological dynamic analysis of network multimedia technology, this study analyzes the construction and teaching circumstances of the platform, and then uses principal component analysis to analyze students’ political theory, political attitude, civilized etiquette, observance of thought, collective thought, public welfare thought, analysis of learning ideas, get the eigenvalues and variance %, of which the proportion of variance of the first four principal components exceeds 90%; public welfare activities and the idea of abiding by laws and regulations have a better influence on the first main component; collective thinking has a comparison on the impact of the second principal component, the correlation between the indicators of thought-political education and the concept of students’ quality is greater than 0.75; it shows that each index has a large degree of correlation with the concept of students’ quality, among which Political attitudes have the greatest impact on students’ quality outlook, with a correlation coefficient of 0.911; secondly, using a nonhomogeneous hidden Markov model to analyze ideological dynamics, we can get the learning situation in different ideological states; finally, the hot spots during the epidemic are related to ideological dynamics Sexual analysis showed that the p values were all less than 0.05, and the correlation analysis between hotspots and ideological dynamics during the epidemic was significant, namely “national sentiments”, “social responsibility”, “angels in white”, “Chinese power”, and “the benevolence of doctors”. …”
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Particle-bound PAHs and Chemical Composition, Sources and Health Risk of PM2.5 in a Highly Industrialized Area by Elizabeth Vega, Diego López-Veneroni, Omar Ramírez, Judith C. Chow, John G. Watson

“…Six factors derived from Principal Component Analysis (PCA) explained ~85% of the PM2.5 variance. …”
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Identifying Optimal Variables to Predict Soil Organic Carbon in Sandy, Saline, and Black Soil Regions: Remote Sensing, Terrain, or Climate Factors? by Liping Wang, Huanjun Liu, Xiang Wang, Xiaofeng Xu, Liyuan He, Chong Luo, Yong Li, Xinle Zhang, Deqiang Zang, Shufeng Zheng, Xiaodan Mei

“…To address this issue, we used the principal component analysis (PCA) method for the feature selection of bands, spectral indexes, and terrain factors for each region. …”
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Enhancing Royal grape quality through a three-year investigation of soil management practices and organic amendments on berry biochemistry by Ozkan Kaya, Sinem Karakus, Fadime Ates, Selda Daler, Harlene Hatterman-Valenti

“…Antioxidant enzyme activities were significantly enhanced under chisel tillage combined with broccoli fertilizer treatment, leading to optimal superoxide dismutase (1426.54 EU) and peroxidase (14,936.81 EU) activities. Principal component analysis revealed that the first two components explained 51.35% of total variance, with distinct temporal clustering of treatment effects. …”
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Health-Related Quality of Life Subdomains in Patients with Parkinson’s Disease: The Role of Gender by Anja Ophey, Carsten Eggers, Richard Dano, Lars Timmermann, Elke Kalbe

“…Therefore, our aim was to reevaluate the PDQ-39 structure and to further explore determinants of HrQoL in PD. 245 PD patients (age: M = 69.64, SD = 8.43; 62.9% male; H&Y: Md = 3.00; cognitive assessment with PANDA: M = 24.82, SD = 3.57) from the baseline database of the Cologne Parkinson Network were used to reevaluate the dimensionality of the PDQ-39 with a principal component analysis (PCA). Multiple regression analyses were conducted to clarify general and domain-specific relationships between clinical, (neuro)psychological, and sociodemographic variables, gender in particular, and HrQoL. …”
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Spatiotemporal heterogeneity management: Optimizing the critical role of ecosystem services in achieving Sustainable Development Goals by Lingli Zuo, Guohua Liu, Junyan Zhao, Jiajia Li, Shuyuan Zheng, Xukun Su

“…We used correlation analysis, principal component analysis, Geographically and Temporally Weighted Regression model, and self-organizing maps to reveal the spatiotemporal heterogeneity of the impacts of the bundle of ESs on the SDGs and to develop spatial planning and management strategies. …”
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Molecular and Biochemical Mechanisms of Scutellum Color Variation in <i>Bactrocera dorsalis</i> Adults (Diptera: Tephritidae) by Guangli Wang, Weijun Li, Jiazhan Wu, Ye Xu, Zhaohuan Xu, Qingxiu Xie, Yugui Ge, Haiyan Yang, Xiaozhen Li

“…Single-nucleotide polymorphism (SNP) annotation showed that there were 17,580 non-synonymous mutation sites located in the exonic region. Principal component analysis based on independent SNP data revealed that the SNPs with LYS were more similar to that with YS when compared with WS. …”
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Effectiveness of an E-Nose Based on Metal Oxide Semiconductor Sensors for Coffee Quality Assessment by Yhan S. Mutz, Samara Mafra Maroum, Leticia L. G. Tessaro, Natália de Oliveira Souza, Mikaela Martins de Bem, Loyane Silvestre Alves, Luisa Pereira Figueiredo, Denes K. A. do Rosario, Patricia C. Bernardes, Cleiton Antônio Nunes

“…Exploratory analysis with principal component analysis (PCA) pointed to a fair grouping of the tested samples according to their specification, indicating the potential of the volatiles in grouping the samples. …”
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Characterization and Selection of WiFi Channel State Information Features for Human Activity Detection in a Smart Public Transportation System by Roya Alizadeh, Yvon Savaria, Chahe Nerguizian

“…Since the environment of a transportation system changes dynamically and non-deterministically, we propose analyzing these changes with a heuristic algorithm that leverages a decision tree to automate a decision-making solution for feature selection. Principal Component Analysis (PCA) is performed before the decision tree algorithm. …”
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Analyzing Drivers of Tropical Moist Forest Dynamics in the Kahuzi-Biega National Park Landscape, Eastern Democratic Republic of Congo from 1990 to 2022 by Nadège Cizungu Cirezi, Jean-François Bastin, Yannick Mugumaarhahama, Yannick Sikuzani Useni, Katcho Karume, Raymond Sinsi Lumbuenamo, Jan Bogaert

“…This included meshing, multi-scale analysis, principal component analysis, zoning, multiple linear regression, and relative importance analysis through bootstrapping. …”
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Potential toxic elements in surface water of Mokosh Beel, Gazipur, Bangladesh: Ecological and human health risk assessment for recreational users by Md. Shahriar Mahmud, M. Safiur Rahman, S.A. Dina, M. Rifat Nasher, Tasrina R. Choudhury, Bilkis A. Begum, Abdus Samad

“…The Nemerow pollution index indicated mild to moderate pollution, while the heavy metal pollution index (HPI) and heavy metal evaluation index (HEI) suggested a low degree of pollution at most sampling sites. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) linked the majority of PTEs to industrial sources, particularly from tannery, leather, and paint industries. …”
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Diversity of Picea omorika (Pančić) Purk. Populations Based on Morpho-anatomical Needle Traits and Bioclimatic Parameters by Biljana Nikolić, Nemanja Rajčević, Zorica Mitić, Sanja Jovanović, Nevena Čule, Katarina Mladenović, Marija Marković, Petar Marin

“…Multivariate analyses separated populations into two main groups. Both principal component analysis and discriminant analysis indicated population overlap, while cluster analysis identified three main groups. …”
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Application of deep learning models on single-cell RNA sequencing analysis uncovers novel markers of double negative T cells by Tian Xu, Qin Xu, Ran Lu, David N. Oakland, Song Li, Liwu Li, Christopher M. Reilly, Xin M. Luo

“…Conventional machine learning approaches such as principal component analysis have been employed in single-cell RNA sequencing (scRNA-seq) analysis to characterize DNT cells. …”
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Metabolite profile and antioxidant activities of Trikatu, black pepper, Javanese long pepper, and red ginger essential oils by Dewa Ayu Ika Pramitha, Tati Herlina, Iman Permana Maksum, Ari Hardianto, Abd. Wahid Rizaldi Akili, Jalifah Latip

“…Phytochemical profiling was carried out by gas chromatography-mass spectrometry (GC–MS). Principal Component Analysis (PCA) was performed with the help of R packages of factoMiner and factoExtra to examine the metabolite distributions. …”
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Genetic Variability, Character Association, Path Coefficient, and Diversity Analysis of Rice (Oryza sativa L.) Genotypes Based on Agro-Morphological Traits by Shubh Pravat Singh Yadav, Sujan Bhandari, Netra Prasad Ghimire, Dipesh Kumar Mehata, Soni Kumari Majhi, Susmita Bhattarai, Samaz Shrestha, Bishnu Yadav, Pratima Chaudhary, Sangita Bhujel

“…This study aimed to determine the genetic diversity by principal component analysis (PCA) and cluster analysis, as well as to assess the path coefficient (PC), genetic deviation, and character association based on grain yield (GY) and other yield-attributing variables. …”
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Systems immunology integrates the complex endotypes of recessive dystrophic epidermolysis bullosa by Nell Hirt, Enzo Manchon, Qian Chen, Clara Delaroque, Aurelien Corneau, Patrice Hemon, Safaa Saker-Delye, Pauline Bataille, Jean-David Bouaziz, Emmanuelle Bourrat, Alain Hovnanian, Helene Le Buanec, Fawzi Aoudjit, Hicham El Costa, Nabila Jabrane-Ferrat, Reem Al-Daccak

“…Artificial intelligence prediction models and principal component analysis stress that RDEB is not solely confined to cutaneous issues but has complex systemic endotypes marked by immune dysregulation and hyperinflammation. …”
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