Bimodal Patterns of Locomotor Activity and Sleep in Drosophila: A Model for Their Simulation by Putilov AA, Verevkin EG, Petrovskii DV, Zakharenko LP

“…Here, we tested whether a similar model could be applied to simulate the bimodal 24-h rhythm of fly locomotor activity and sleep.Methods: To obtain typical curves for the simulations, a sample of 4263 individual 24-h curves of locomotor activity and sleep were subjected to principal component analysis. It yielded three principal components, which explained more than 70% of the individual variations in these curves. …”
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Predicting purification process fit of monoclonal antibodies using machine learning by Andrew Maier, Minjeong Cha, Sean Burgess, Amy Wang, Carlos Cuellar, Soo Kim, Neeraja Sundar Rajan, Josephine Neyyan, Rituparna Sengupta, Kelly O’Connor, Nicole Ott, Ambrose Williams

“…Here, we describe a QSPR strategy for in silico monoclonal antibody purification process fit assessment. Principal Component Analysis is applied to extract a one-dimensional basis for comparison of molecular chromatographic binding behavior from multi-dimensional high-throughput batch-binding screen data. …”
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Characterization of an Endemic Plant Origanum grosii from Morocco: Trace Element Concentration and Antihyperglycemic Activities by H. El hassouni, M. Bouhrim, R. El hajji, M. Bnouham, A. Ziyyat, A. Romane

“…This characterization was realized by determining the concentration of metals in different parts of the plant (flowers, leaves, and stems) by ICP-MS, and the results were studied statistically by Principal Component Analysis (PCA). Phytochemical screening with the dosage of polyphenols and flavonoids has been conducted. …”
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Enhanced Multi‐Objective Optimization Model for Bridge Performance Assessment and Prediction, Based on Improved PCA, K‐Means Clustering, and Kaplan–Meier Survival Algorithm by Chengzhong Gui, Zhi Duan, Zuwei Huang, Zhiguo Sun, Wei Qiao, Yu Cheng

“…It focuses on the processing of multi‐source heterogeneous data, selection of key sub‐parameters using Principal Component Analysis (PCA), enhanced K‐means clustering analysis, determination of structural component target thresholds, time‐dependent survival probability analysis, regression fitting, and timing prediction of the bridge system for both the components of double‐layer truss arch bridge and the bridge system. …”
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Diversity Assessment of Some Sesame (Sesamum indicum L.) Genotypes Cultivated in Northern Ghana Using Morphological and Simple Sequence Repeat (SSR) Markers by Raphael Adu-Gyamfi, Ruth Prempeh, Issahaku Zakaria

“…Data collected were subjected to Principal Component Analysis (PCA) and a dendrogram showing similarity between the accessions were drawn. …”
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Hydrogeochemical characterization of groundwater using water quality index and multivariate statistical analysis in Binji town and environs, Sokoto basin, Northwestern Nigeria by Ibrahim Mohammed Abdullahi, Lawali Abubakar, Garba Saidu, Hassan Yusuf

“…Correlation analysis gave a moderate positive correlation that ranges from 0.632 to 0.659 between total hardness, Mg and HCO3, and that between Mg and HCO3 indicates the contribution of these elements to the hardness of water. Principal component analysis gave six components with a total variance of 76.19% with eigenvalues above 1 with the range of 1.52 – 4.26. …”
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Physical activity patterns in a representative sample of adolescents from the largest city in Latin America: a cross-sectional study in Sao Paulo by Maria Fernanda Tourinho Peres, Gerson Ferrari, Leandro F.M. Rezende, Gabriela Arantes Wagner, Alex A Florindo

“…Socioeconomic status was assessed using a wealth index derived from principal component analysis. Descriptive analyses evaluated differences in total and domain-specific PA by sex, socioeconomic status and maternal education level.Outcome measures We collected data on the frequency and duration that adolescents spent in each PA domain (active transportation, leisure PA and physical education classes) through a self-report questionnaire.Results On average, adolescents spent 197.7 min/week (95% CI 190.6–204.8) in total PA. …”
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Tomato fruit quality and nutrient dynamics under water deficit conditions: The influence of an organic fertilizer. by Maryam Zahedifar, Ali Akbar Moosavi, Edris Gavili, Arash Ershadi

“…Maya) were investigated in greenhouse conditions based on bi-plot and principal component analysis (PCA). Plants which were cultivated in soil under greenhouse conditions were subjected to four levels foliar spraying of Zargreen liquid organic fertilizer, ZLOF (0, 2.5, 5, and 7.5 L 1000-1, shown as Z0, Z2.5, Z5, and Z7.5, respectively), and three levels of soil water, SW (100, 75, and 50% of field capacity (FC), shown W100, W75, and W50, respectively). …”
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Application of multi-indexing approach within a GIS framework to investigate the quality and contamination of ground water in Barisal sadar, Bangladesh by Md. Numan Hossain, M. Farhad Howladar, Sohag Ahammed, Md Rezwanul Haque, Majedul Islam Khan, Muyeed Hasan, Tayabur Rashid Chowdhury, Alamgir Hosain

“…The significant positive correlations among EC, TDS, TH, turbidity, salinity, NaCl, chloride, and calcium ions as per correlogram, principal component analysis (PCA) biplot, and heat map clustering, indicating similar sources of origin. …”
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Effect of 5-Aminolevulinic Acid on the Quality and Volatile Metabolites of Korla Fragrant Pear Fruit by SUN Tianyu, WEN Bo, WANG Chunfeng, TIAN Jia, HAO Zhichao, LIN Yan, WEN Yue, ZHANG Feng

“…Meanwhile, comprehensive quality evaluation of pear fruit under 5-ALA treatment was carried out using principal component analysis (PCA), and the optimal 5-ALA concentration for improving the fruit quality was determined. …”
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Comparison of the lower genital tract microbiome composition in patients with benign gynecological disease by Yonghui Shi, Jun Li, Jinjing Xie, Tianye Yang, Qiongyan Ma, Hua Chen, Wenwei Guo

“…The richness and evenness of the microbiome were generally consistent among the HW, EP, UM, and OC groups. Principal component analysis (PCA), principal coordinate analysis (PCoA) and nonmetric multidimensional scaling (NMDS) revealed no distinct separation trends among the four groups. …”
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Exploring the burden of cholera in the WHO African region: patterns and trends from 2000 to 2023 cholera outbreak data by Joseph Okeibunor, Saliou Diallo, Abdou Salam Gueye, Etien Luc Koua, Jean Paul Kimenyi, Vincent Dossou Sodjinou, Fleury Hybriel Moussana, Freddy Kambale

“…We cross-referenced several WASH indicators, and generated a similarity matrix to categorise countries or subnational units into groups using principal component analysis and K-means clustering. We integrated cholera outbreak data with WASH indicators and created a matrix of indicators relevant for analysing cholera burden. …”
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Early Detection of Verticillium Wilt in Cotton by Using Hyperspectral Imaging Combined with Recurrence Plots by Fei Tan, Xiuwen Gao, Hao Cang, Nianyi Wu, Ruoyu Di, Jingkun Yan, Chengkai Li, Pan Gao, Xin Lv

“…In order to reduce redundant information between features, principal component analysis (PCA) was used to extract the first five principal components, which explained 99.02% of the information from the 11 features. …”
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Assessing Genetic Diversity and Population Structure of Western Honey Bees in the Czech Republic Using 22 Microsatellite Loci by Aleš Knoll, Martin Šotek, Jan Prouza, Lucie Langová, Antonín Přidal, Tomáš Urban

“…Cluster and DAPC (discriminant analysis principal component) analysis classified the bee samples collected from across the country into three and five to six distinguishable groups, respectively. …”
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Estimation of daily groundwater evapotranspiration from diurnal variations of lysimeter experiments data in an arid zone by Peng Yao, Fengzhi Shi, Yuehui Wang, Ningze Dai, Chengyi Zhao

“…Variations at hourly and daily scales were analyzed, and a modified White method was applied to estimate ETg. Principal component analysis and a random forest model were used to assess meteorological influences. …”
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Improved Estimation of Aboveground Biomass in Rubber Plantations Using Deep Learning on UAV Multispectral Imagery by Hongjian Tan, Weili Kou, Weiheng Xu, Leiguang Wang, Huan Wang, Ning Lu

“…The results indicate that the RFR combined with a principal component analysis (PCA) for feature selection yielded the best performance (<i>R</i>² = 0.81, <i>RMSE</i> = 11.63 t/ha, <i>MAE</i> = 9.27 t/ha) between the three ML algorithms. …”
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Morpho-meristic variations of the native and Vietnam-originated climbing perch (Anabas testudineus), collected from hatchery sources in Bangladesh by Md. Arif Shahariar, Md. Mahamudul Hassan, Swagata Aditya, Tanjina Saulin, Atika Khondokar, Mohammad Shafiqul Alam

“…The nonparametric Kruskal Wallis (H) test also revealed significant variation both in morphometric and meristic characteristics. Principal component analysis indicated that native and Vietnam-originated climbing perch can be distinguished from one another using the two distinctive morphological parameters-total length (TL) and PVFL. …”
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An experimental and modelling approach to proclaim sustainable machining using avocado oil-based nano-cutting fluids by Abera Ayza Anebo, Venkatesh Chenrayan, Kiran Shahapurkar, Gezahgn Gebremaryam, Jana Petrů, Manzoore Elahi M. Soudagar, Vijayabhaskara Rao Bhaviripudi, Rajakrishnan Rajagopal, Muhammad Nasir Bashir

“…A hybrid Grey Relational Analysis (GRA) coupled with Principal Component Analysis (PCA) was followed to scrutiny the effect of novel machining fluid on machining objectives. …”
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Synergistic effects of chemical and biochemical fertilization on yield enhancement and oil quality optimization in ‘Zard’ olive cultivars by Mohammad Saeed Tadayon, Ahmad Asgharzadeh, Seyed Majid Mousavi, Kobra Saghafi

“…The second factor, biological fertilizer application (BF), also comprised three levels: BF0 (control), soil-applied organic fertilizer without biological agents; BF1, which included a soil application of an organic fertilizer mix, mycorrhizal fungi, and the beneficial bacteria Bacillus subtilis and Pseudomonas fluorescens, supplemented with fulvic acid and amino acids; and BF1+BFF, where trees were treated with both soil and foliar applications of the aforementioned bacterial species, fulvic acid, and amino acids.ResultsThe CF100+BF1+BFF treatment significantly increased fruit length (31.14%), diameter (41.61%), flesh thickness (30.48%), fresh weight (38.76%), dry weight (55.68%), and yield per tree (27.00%) compared to the control (CF100+BF0). Principal Component Analysis (PCA) identified CF100+BF1+BFF, CF75+BF1+BFF, and CF50+BF1+BFF as superior treatments for fruit characteristics, while CF50+BF1+BFF excelled in oil quality indicators.ConclusionThe study recommends the CF75+BF1+BFF and CF50+BF1+BFF treatments for concurrent improvements in fruit and oil quality. …”
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Water–saving irrigation combined with N–loaded clinoptilolite enhances nutrient yield, and water productivity by improving rice root characteristics: A combined PCA–SEM analysis... by Yang Sun, Qi Wu, Daocai Chi, Hongyang Chen, Suyun Zhu, Qingliang Liu

“…We employed principal component analysis (PCA) and structural equation modeling (SEM) to analyze the interactions among the factors. …”
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