THE TECHNOLOGY OF BUDGETING ENTERPRISES WITH THE DIVISIONAL STRUCTURE by Inna Kuznetsova, Yuliya Karpenko

“…The following tasks are solved in the article: the composition of budgeting technology is justified; the income generation model for an enterprise with a divisional structure is improved; the system of obligatory indicators of an enterprise with the divisional structure is suggested as well as the information model of budgeting the income of the cost centre of the second type. …”
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ML-based top taggers: Performance, uncertainty and impact of tower & tracker data integration by Rameswar Sahu, Kirtiman Ghosh

“…Nevertheless, the LLF-based classifiers trained on constituents' 4-momentum data exhibit substantial dependency on the jet modeling within Monte Carlo generators. The composite classifiers, formed by stacking a BDT on top of a GNN/CNN, not only enhance the performance of LLF-based classifiers but also mitigate the uncertainties stemming from the showering and hadronization model of the event generator. …”
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Unveiling the effects of metabolites on the material properties of natural rubber by the integration of metabolomics and material characteristics by Nobuyuki Hiraoka, Shunsuke Imai, Shintaro Shioyama, Fuminori Yoneyama, Akio Mase, Yuko Makita

“…Correlation analysis between the metabolites and the properties of NR indicated that different metabolites affected different properties. A regression model of NR properties using metabolites as the explanatory variables suggests that about five metabolites need to be considered when examining the relationship between properties and metabolites. …”
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C-Reactive Protein-to-Serum Chloride Ratio: A Novel Marker of All-Cause Mortality in Maintenance Haemodialysis Patients by Francisco Valga, Tania Monzón, José C. De la Flor, Angelo Santana-del-Pino, Nicanor Vega-Díaz, Ana Yurena Sanchez-Santana, Gloria Antón-Pérez, Sergio Ruiz-Santana, José C. Rodríguez-Pérez, Patricia Perez-Borges

“…Variables included in the model were selected using a stepwise selection procedure based on the corrected Akaike information criterion (AICc), which balances model fit and complexity. …”
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Providing a Roadmap for the Adaption of Agricultural Sector to Water Scarcity Conditions (Case Study: Selected Crops of Tajan Basin, Iran) by H. Fouladi, H. Amirnejad, S. Shirzadi Laskookalayeh

“…The model must also include decision variables that affect those objectives, and constraints that limit what user can do. …”
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Production of Biodiesel from Mixed Castor Seed and Microalgae Oils: Optimization of the Production and Fuel Quality Assessment by Dejene Beyene, Mohammedsani Abdulkadir, Adisu Befekadu

“…Experimental results were analyzed by response surface regression to produce a model for predicting biodiesel yield. Model significance, fitness, the effect of significant variables, and interactions between the variables on the yield of biodiesel were studied through the analysis of variance (ANOVA). …”
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Travel Matrix Decomposition for Understanding Spatial Long-Distance Travel Structure by Hiromichi Yamaguchi, Mashu Shibata, Shoichiro Nakayama

“…They can be interpreted as composite indicators of several variables that are treated in the travel-destination choice multinomial logit model. …”
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Predicting iron contents in the Tamra-Douahria mining site using a deep neural network approach by Zohra Kraiem, Fathi Maalaoui, Salah Bouhlel, Chaouki Sadik, Ali Sdiri

“…The well-known Douahria-Tamra mining site is characterized by the presence of deposits with high variability in composition, colour, and structural-textural peculiarities, especially in the exploitable layers. …”
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Optimization of a fermented pumpkin-based beverage to improve Lactobacillus mali survival and α-glucosidase inhibitory activity: A response surface methodology approach by W.Y. Koh, U. Uthumporn, A. Rosma, A.R. Irfan, Y.H. Park

“…The aim of this research was to develop an optimum fermentation and composition model for a new fermented pumpkin-based beverage with high probiotic survival and α-glucosidase inhibitory activity. …”
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CMIP6 GCMs Projected Future Koppen‐Geiger Climate Zones on a Global Scale by Young Hoon Song, Eun‐Sung Chung, Brian Odhiambo Ayugi

“…Consequently, the climate variables from GCMs were overestimated compared to the reference data, and the composition of the climate zones was less complex. …”
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Vegetation Succession Patterns at Sperry Glacier’s Foreland, Glacier National Park, MT, USA by Ami Bryant, Lynn M. Resler, Dianna Gielstra, Thomas Pingel

“…GIS-derived variables contextualized the plots’ aspect, terrain roughness, topographic position, solar radiation, and curvature. …”
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Multitemporal Sentinel and GEDI data integration for overstory and understory fuel type classification by Pegah Mohammadpour, Domingos Xavier Viegas, Alcides Pereira, Emilio Chuvieco

“…Wildfires significantly reshape the landscape of the Mediterranean basin, altering forest composition, structure, and diversity. Consequently, detailed fuel mapping is crucial for improving fire risk assessment and enhancing fire behavior modeling, as wildfires typically ignite from surface fuels and may spread vertically to canopy fuels due to canopy fuel continuity. …”
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Chemical Diversity of UK-Grown Tea Explored Using Metabolomics and Machine Learning by Amanda J. Lloyd, Alina Warren-Walker, Jasen Finch, Jo Harper, Kathryn Bennet, Alison Watson, Laura Lyons, Pilar Martinez Martin, Thomas Wilson, Manfred Beckmann

“…The intraclass variability in leaf composition was similar between the varieties. …”
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Numerical Mixing Index: Definition and Application on Concrete Mixer by Cristian Ferrari, Nicolò Beccati, Luca Magri

“…In this work, a statistical method is applied to a multiphase CFD simulation of concrete mixing performed in a truck mixer. The numerical model is based on an Eulerian–Eulerian approach in a transient regime. …”
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Is the real sector structure the determining factor of the financial sector structure of Iran's economy? by Seyedrohollah Ahmadi Hajiabadi

“…In the second step, the long-term and short-term model coefficients were estimated and then using causality test, the causal relationship between the structure of the financial and real sectors was investigated. …”
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Biofuel Production in Oleic Acid Hydrodeoxygenation Utilizing a Ni/Tire Rubber Carbon Catalyst and Predicting of n-Alkanes with Box–Behnken and Artificial Neural Networks by Luis A. Sánchez-Olmos, Manuel Sánchez-Cárdenas, Fernando Trejo, Martín Montes Rivera, Ernesto Olvera-Gonzalez, Benito Alexis Hernández Guerrero

“…We developed a dataset with pressure, temperature, metal content, reaction time, and catalyst composition variables as inputs. The output variables are the n-C₁₇ and n-C₁₈ alkanes obtained. …”
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A novel data processing approach to detect fraudulent insurance claims for physical damage to cars by Ahmet Yücel

“…To this end, Singular Value Decomposition-based components and correlation-based composite variables were created. Machine learning models were then developed, with predictors and composite variables selected based on standard feature selection procedures. …”
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Crustacean zooplankton communities as indicators of game fish occurrence and abundance in Québec lakes by Cindy Paquette, Stéphanie Gagné, Maxime Gaudet-Boulay, Véronique Leclerc, Paschale Noël Bégin, Zofia E. Taranu, Beatrix E. Beisner, Vincent Fugère

“…Our analyses revealed that both taxonomic and functional zooplankton composition were significant predictors of focal fish species occurrence, albeit less so than environmental or fish community composition variables. …”
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Canada goose fecal microbiota correlate with geography more than host‐associated factors by Joshua C. Gil, Heather R. Skeen, Celeste Cuellar, Sarah M. Hird

“…Supervised machine learning models were able to predict the state and flyway of origin of a fecal sample based on bacterial composition alone. …”
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Lactational performance effects of 3-nitrooxypropanol supplementation to dairy cows: A meta-regression by L.F. Martins, M. Maigaard, M. Johansen, P. Lund, X. Ma, M. Niu, A.N. Hristov

“…Full models containing uncorrelated explanatory variables (Pearson correlation <0.50) were fitted, and variables were removed from the final model if nonsignificant using the stepwise selection approach. …”
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