Modeling and Reconstruction of Mixed Functional and Molecular Patterns

“…The computational algorithm is based on a latent variable model whose parameters are estimated using clustered component analysis. …”
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Influence of root canal sealer composition on postoperative pain after endodontic treatment of permanent teeth: a systematic review and meta-analyses by Vania Gomes Moraes, Sandra Regina Santos Meyfarth, Guido Artemio Maranón-Vásquez, Lívia Azeredo Alves Antunes, Leonardo Santos Antunes

“…Sealer extrusion is a variable that requires further studies. KEYWORDS Postoperative pain; Root canal treatment; Sealer composition; Sealer extrusion; Systematic review. …”
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Modeling and Reconstruction of Mixed Functional and Molecular Patterns by Yue Wang, Jianhua Xuan, Rujirutana Srikanchana, Peter L. Choyke

“…The computational algorithm is based on a latent variable model whose parameters are estimated using clustered component analysis. …”
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Regression Models for Predicting Physicochemical Properties of Biochar by Chiaw Hui Chiew, Li Yee Lim, Pei Ying Ong, Chunjie Li, Yee Van Fan

“…However, properties like CEC and Specific Surface Area (SSA) presented challenges due to inconsistencies between high R² and higher Root Mean Square Error (RMSE) values, indicating underlying variability. Municipal Solid Waste (MSW) biochar was the most challenging to predict due to its heterogeneous composition. …”
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Exploring the link between age at menarche, anthropometry and body fat composition with type II diabetes in a Singapore multi-ethnic cohort by Paula Benny, Qian Yang, Beverly Wen-Xin Wong, Cuilin Zhang, Eu-Leong Yong, Ling-Jun Li, Zhongwei Huang

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Landscape and climatic factors shaping mosquito abundance and species composition in southern Spain: A machine learning approach to the study of vector ecology by Martina Ferraguti, Sergio Magallanes, Carlos Mora-Rubio, Daniel Bravo-Barriga, Florentino de Lope, Alfonso Marzal

“…This study explores the interaction between environmental and climate factors, investigating their influence on the abundance and species composition of mosquitoes in southwestern Spain, a region endemic to several mosquito-borne diseases.Using comprehensive field data from 2020, we analysed mosquito abundance and species richness alongside remote sensing variables and modeling techniques, including the machine learning Random Forest. …”
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Shibboleth: An agent-based model of signalling mimicry. by Jonathan R Goodman, Andrew Caines, Robert A Foley

“…Here, we run five different versions of a 'Shibboleth' model: a first, simple version, which evaluates whether a composite variable of mimicry quality and detection quality is a superior predictor to the model's outcome than is cost of detection. …”
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Coach-Assisted eHealth With Group or Individual Support for Employees With Obesity: Randomized Controlled Trial on Weight, Body Composition, and Health Metrics by Siniriikka A Männistö, Kirsi H Pietiläinen, Joona Muotka, Laura-Unnukka Suojanen, Raimo Lappalainen, Riitta Korpela

“…ConclusionsThere were no differences in weight or other somatic health variables between the eHealth arm and intervention combining eHealth with minimal group or individual enhancement. …”
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Evolutionary conformation model of salivary gland lithiasis by Álvaro Sánchez Barrueco, Álvaro Sánchez Barrueco, Álvaro Sánchez Barrueco, María Victoria López-Acevedo Cornejo, William Aragonés Sanzen-Baker, William Aragonés Sanzen-Baker, William Aragonés Sanzen-Baker, Sol López-Andrés, Gonzalo Díaz Tapia, Gonzalo Díaz Tapia, Gonzalo Díaz Tapia, Ignacio Alcalá Rueda, Ignacio Alcalá Rueda, Ignacio Alcalá Rueda, Jessica Mireya Santillán Coello, Jessica Mireya Santillán Coello, Jessica Mireya Santillán Coello, Carlos Cenjor Español, Carlos Cenjor Español, Carlos Cenjor Español, José Miguel Villacampa Aubá, José Miguel Villacampa Aubá, José Miguel Villacampa Aubá

“…The coexistence of amorphous phases and structural heterogeneity within layers explains the variability among stones. Detailed SEM-EDX analysis supports a unified conformational model for sialoliths that integrates the interplay of organic substrates, inorganic minerals, bacterial biofilms, and temporal factors.ConclusionsSialoliths are oolitic aggregates featuring a central core surrounded by concentric layers composed of organic and inorganic materials. …”
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The influence of whole grain products and red meat on intestinal microbiota composition in normal weight adults: a randomized crossover intervention trial. by Jana Foerster, Gertraud Maskarinec, Nicole Reichardt, Adrian Tett, Arjan Narbad, Michael Blaut, Heiner Boeing

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Recovery of Carbon Fibres From Aged Epoxy Matrix Composites Using H2O2 as an Oxidant: A Thermodynamic and Technoeconomic Analysis by Paul Njeni Mabalane, Kristof Molnar, Philani Thembelihle Mazibuko, Kolos Molnár, Caroline Khoathane, Mike Masukume

“…The price of hydrogen peroxide and recovered carbon fibre are essential variables that have a high effect on the model.…”
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Novel bio-adsorbent of alginate/HTC hydrochar & alginate/HTH hydrochar composite beads for removal of basic blue 9 from water by Nayereh.S Tadayoni, Mohammad Dinari

“…The performance of the adsorbents was evaluated based on variables including pH, dosage of adsorbent, dye concentration, and duration of adsorption. …”
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Physical characteristics as indicators of performance in young alpine skiers in Super-G by Stojan Puhalj, Blaž Lešnik, Črtomir Matejek, Samo Fošnarič, Tjaša Kmet, Jurij Planinšec

“…The multiple regression model explained 73% of the variance in the boys' performance and 59% in the girls', although the model itself was not statistically significant for predicting performance. …”
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Uncertainty and Stochasticity in Modelling of Microstructure Evolution During Hot Rolling of Steels Uncertainty and Stochasticity in Modelling of Microstructure Evolution During Ho... by D. Szeliga, J. Foryś, J. Kusiak, R. Kuziak, R. Nadolski, M. Pietrzyk, Ł. Rauch

“…Models based on stochastic internal variables meet this requirement. …”
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Integrating piecewise and symbolic regression with remote sensing data for spatiotemporal analysis of surface water total dissolved solids in the Karun River, Iran by Javad Zahiri, Mohammad Reza Nikoo, Adell Moradi-Sabzkouhi, Mitra Cheraghi, Nazmi Mat Nawi

“…The innovative use of a fuzzy-based uncertainty analysis, coupled with AHP weighting, allowed for a comprehensive assessment of TDS estimation accuracy and uncertainty. The Composite Uncertainty Index (CUI) approach revealed that the Multivariate Adaptive Regression Splines (MARS) and M5 models performed better than other models, with CUI values of 0.83 and 0.72, respectively. …”
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Performance Evaluation and Optimization of Binder-Toner and Mixing Efficiency Ratios in an E-Waste Toner-Modified Composite Mixture Using Response Surface Methodology by Syyed Adnan Raheel Shah, Sabahat Hussan, Nabil Ben Kahla, Muhammad Kashif Anwar, Mansoor Ahmad Baluch, Ahsan Nawaz

“…The study utilized a central composite design (CCD) together with the response surface methodology (RSM) to optimize the mix design variables, specifically the binder-toner ratio (BT) and mixing efficiency ratio (MER). …”
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Lis State of the Greenland and Barents Sea ice cover in the context of current climate change by Ye. U. Mironov, E. S. Egorova, N. A. Lis

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A novel method for predicting the geochemical composition of tailings with laboratory field and hyperspectral airborne data using a regression and classification-based approach by Yaron Ogen, Michael Denk, Cornelia Glaesser, Holger Eichstaedt

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Fine-scale landscape characteristics, vegetation composition, and snowmelt timing control phenological heterogeneity across low-Arctic tundra landscapes in Western Alaska by Dedi Yang, Wouter Hantson, Daniel J Hayes, Jin Wu, Shawn P Serbin

“…Deciduous tall shrubs (e.g. alder and willow) had a later SOS (∼7 d behind the mean of other PFTs), but completed leaf expansion (within 2 weeks) considerably faster compared to other PFTs. We modeled the landscape-scale variation in SOS and SOF using Random Forest, which showed that plant phenology can be accurately captured by a suite of variables related to vegetation composition, topographic characteristics, and snowmelt timing (variance explained: 53%–68% for SOS and 59%–82% for SOF). …”
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Review: Preclinical Models of Large‐Vessel Occlusion Stroke by Alexander Keister, Arianna Carfora, Mayur S. Patel, Amanda S. Zakeri, Lillian Mannix, Debra G. Wheeler, Paco S. Herson, Shahid M. Nimjee

“…Thus, variables including size and region of the occlusion, composition of the clot, and degree of reperfusion can be controlled. …”
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