Human Health Risk Prediction Method of Regional Atmospheric Environmental Pollution Sources Based on PMF and PCA Analysis under Artificial Intelligence Cloud Model by Shihui Zhang, Xinghua Sun, Naidi Liu, Jing Mi

“…This method takes the 75-day measured environmental receptor data of an area under the artificial intelligence cloud model as the basic data, uses the normrnd () function to expand the receptor data, and uses the positive definite matrix factor analysis (PMF) and principal component analysis (PCA) models to verify the rationality of the data expansion. …”
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Breast myopathy co-occurrence and its impact on carcass and meat quality attributes in broiler chickens by Míriam Muñoz-Lapeira, Maria Font-i-Furnols, Albert Brun, Anna Jofré, Marcos Botella, Cristina Zomeño

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Étude des représentations sociales d’un site classé aménagé : application au site de l’Anse de Paulilles (France) by Valérie Desrochers, Jocelyne Ferraris, Catherine Garnier

“…The results show that there is a correlation between patrimony and Paulilles’ site representations, principally in function of age and place of residence. …”
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Quality evaluation of Polygonatum sibiricum slices from different regions based on appearance traits and multi-index metabolites combined with TOPSIS and gray relation analysis by Cheng Wang, Cheng Wang, Ju Ye, Sisi Jiang, Sisi Jiang, Xuguang He, Xuguang He, Min Ma, Min Ma, Li Yin

“…This study focuses on Polygonatum sibiricum slices, aiming to establish a method for its quality evaluation.MethodsThe appearance traits of P. sibiricum slices were quantified, and the contents of six functional metabolites were determined. With eight traits and six metabolite contents as variables, principal component analysis (PCA) and orthogonal partial least-squares discrimination analysis (OPLS-DA) were performed. …”
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Physicochemical and sensory properties of Southern Thai curry pastes by Rajnibhas Sukeaw Samakradhamrongthai, Taruedee Jannu, Tussanun Tongboonchu, Wanalee Sangpimpa, Phatthamon Srichan, Gerry Renaldi, Preeyabhorn Detarun, Sunisa Siripongvutikorn, Tanyarath Utaipan, Thawien Wittaya, Worapanit Chansuwan

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Morphometric analysis of equid cheek teeth using a digital image processor: a case study of the Pleistocene Cedazo local fauna equids, Mexico by Christian Raúl Barrón-Ortiz, Gilfredo de la Riva-Hernández, Raúl Barrón-Corvera

“…Specimens of Equus caballus, E. asinus and hybrids were also included to serve as controls. Principal Components and Canonical Discriminant Functions analyses were performed. …”
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Data-driven diabetes mellitus prediction and management: a comparative evaluation of decision tree classifier and artificial neural network models along with statistical analysis by Idris Zubairu Sadiq, Babangida Sanusi Katsayal, Bashiru Ibrahim, Maryam Ibrahim, Hassan Aliyu Hassan, Umar Muhammad Ghali, Abdullahi Garba Usman, Abubakar Usman, Sani Isah Abba

“…Body Mass Index (BMI) was also notably higher in diabetics, reinforcing the link between obesity and diabetes risk. Principal Component analysis further highlighted five clusters of health-related variables, identifying age-related metabolic indicators (AGE, HbA1c, BMI), kidney function markers (creatinine (Cr), Urea), cardiovascular lipid profiles (Cholesterol, LDL), lipid transport (VLDL), and protective cardiovascular indicator (HDL). …”
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Fluorescence spectral characteristics of DOM and its effects on the bacterial community structure in Bosten Lake, China by Jiali Wang, Chen Li, Wei Wu, Lei Ren, Yuhe Dong

“…The relationships among bacterial communities, DOM fluorescence components, and environmental factors were elucidated through principal component analysis and redundancy analysis. …”
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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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Transformer-based ECG classification for early detection of cardiac arrhythmias by Sunnia Ikram, Amna Ikram, Harvinder Singh, Malik Daler Ali Awan, Sajid Naveed, Isabel De la Torre Díez, Henry Fabian Gongora, Thania Candelaria Chio Montero

“…The pipeline begins with signal preprocessing, where raw ECG data are denoised, normalized, and relabeled for compatibility with attention-based architectures. Principal component analysis (PCA), correlation analysis, and feature engineering is applied to retain the most informative features. …”
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Rice seed integrity evaluation: Developing a rapid onsite system to check seed fraud using a portable NIR spectroscopic device coupled with smartphone technology by Ernest Teye, Charles Lloyd Yeboah Amuah, Vida Gyimah Boadu, Kwadwo Anokye Dompreh, Maxwell Darko Asante, Francis Padi Lamptey, Stephen Narh, Daniel Dzorkpe Gamenyah, George Oduro Nkansah, Selorm Akaba

“…After applying various pre-processing techniques and principal component analysis (PCA), linear discriminant functions 1 and 2 successfully revealed distinct clustering patterns for both the varieties and categories (rice seed and paddy). …”
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Electronic Nose System Based on Metal Oxide Semiconductor Sensors for the Analysis of Volatile Organic Compounds in Exhaled Breath for the Discrimination of Liver Cirrhosis Patient... by Makhtar War, Benachir Bouchikhi, Omar Zaim, Naoual Lagdali, Fatima Zohra Ajana, Nezha El Bari

“…Sensor’s measurement data were analyzed using machine learning techniques, such as principal component analysis (PCA), discriminant function analysis (DFA), and support vector machines (SVMs) that were utilized to uncover meaningful patterns and facilitate accurate classification of sensor-derived information. …”
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Bioactive Polysaccharides from <i>Hericium erinaceus</i>: Extraction, Structure, Bioactivities, and Applications by Fangzhi Ge, Yan Chen, Binshuo Wang, Wenxin Zhou, Baoxiang Du, Lin Hou

“…HEPs exhibit a diverse array of biological activities, including immune enhancement, anti-tumor effects, anti-inflammatory properties, antioxidant capabilities, and antiviral functions. This paper provides a comprehensive review of recent advancements in the extraction, separation, purification, structural analysis, biological activity, and toxicity assessments of HEPs. …”
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Mediating effect of TyG index on the association between glucose-lipid metabolism-related dietary pattern and T2DM: a propensity score-matched analysis by ShuShu Li, Rong Xia, Xing Gong, Chao Wang, Hechun Liu, Huibin Dong, Zhangyao Su, Yucheng Liang, Shoulin Wang, Tao Yang

“…Research design and methods Directed acyclic graphs combined with propensity score matching were used to minimize confounding, resulting in 1330 subjects for final analysis. Principal component analysis and reduced rank regression, applied to eleven food groups. …”
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Evaluation and visualization of multiaxial fatigue behavior under random non-proportional loading condition by Takahiro Morishita, Fumio Ogawa, Takamoto Itoh

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A Multidisciplinary Approach for the Assessment of the Last Surviving ‘Marrone di Chiusa Pesio’ Chestnut Trees in the Piemonte Region (Italy) by Giovanna Neirotti, Alessandro Tomatis, Federica Germanà, Alessia Imparato, Andrea Valisena, Maria Gabriella Mellano, Paola Ruffa, Dario Donno, Daniela Torello Marinoni, Gabriele Loris Beccaro, Giovanni Gamba

“…These included tannins (about 22–28 mg/100 g DW) and cinnamic acids (about 23–25 mg/100 g DW), followed by flavonols, benzoic acids, organic acids, monoterpenes, vitamin C, and catechins, listed in order of predominance. A Principal Component Analysis (PCA) was performed to observe the distribution of the samples and their correlations based on the chemical composition. …”
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Banana Flour Adulteration Key Marker Unravelled by Inductively Coupled Plasma Optical Emission Spectrometry Assisted by Chemometric Tools by Silvio Luiz Fernandes Júnior, Paula Mothé Gonçalves, Diego Barros Batista, Aderval S. Luna, Fernanda Nunes Ferreira, Licarion Pinto, Jefferson Santos de Gois

“…Applying chemometric techniques, such as Principal Component Analysis, Linear Discriminant Analysis, and Partial Least Squares Discriminant Analysis, allowed us to distinguish the authentic samples from the adulterated ones clearly. …”
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Molecular dynamics simulation of wild and mutant proteasome subunit beta type 8 (PSMB8) protein: Implications for restoration of inflammation in experimental autoimmune encephalomy... by Shamrat Kumar Paul, Md Saddam, Nisat Tabassum, Mahbub Hasan

“…The differences in the protein's overall motion and the atoms' precise location are identified by the principal component analysis, showing that the overall motion and location of the atoms are different. …”
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Sistemas de drenagem agrícola. Parte I: desenvolvimento do modelo e análise de sensibilidade Agricultural drainage systems. Part I: model development and sensitivity analysis by João C. F. Borges Júnior, Paulo A. Ferreira, Fernando F. Pruski, Aziz G. da Silva Júnior

“…Using the production functions that consider the stress caused by excess and lack of water in the root zone, this model accomplishes the economic analysis for several configurations of the drainage system, allowing for the determination of the economic spacing among drains besides informing about the economic viability of the enterprise. …”
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Biochemical and Raman spectroscopic insights into plant-mold interactions by Ayse SEN, Muhammad AHMED, Omar DARKAZANLI, Duygu GOKSAY-KADAIFCILER, Feyza GUZELCIMEN

“…To validate these findings, advanced multivariate techniques such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) were employed, achieving high accuracy in distinguishing mold-infected samples from controls. …”
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