TROLL 4.0: representing water and carbon fluxes, leaf phenology, and intraspecific trait variation in a mixed-species individual-based forest dynamics model – Part 2: Model evaluat... by S. Schmitt, S. Schmitt, S. Schmitt, F. J. Fischer, J. G. C. Ball, N. Barbier, M. Boisseaux, D. Bonal, B. Burban, X. Chen, G. Derroire, G. Derroire, G. Derroire, J. W. Lichstein, D. Nemetschek, N. Restrepo-Coupe, S. Saleska, G. Sellan, P. Verley, G. Vincent, C. Ziegler, J. Chave, I. Maréchaux

“…The simulated canopy height distribution showed a high correlation coefficient (CC) with observed aerial and satellite data (CC <span class="inline-formula">&gt;</span> 0.92), while the species and functional composition were well represented (CC <span class="inline-formula">&gt;</span> 0.75). …”
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Novel pyrochlores in the Bi2O3–MgO–Ta2O5 (BMT) system: Synthesis optimisation, phase equilibria and dielectric properties by K.B. Tan, P.Y. Tan, Y. Feng, C.C. Khaw, V. Raman, H.C. Ananda Murthy, R. Balachandran, S.K. Chen, O.J. Lee, K.Y. Chan, D. Zhou, M. Lu

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Coordination of technology of railway operation of the Republic of Tajikistan and organization of railways in international traffic by P. N. Pulatov

“…Proposed classification of technological restrictions and controlled variables in the performance of transport takes into account methods for changing external conditions for the functioning of the railway landfill and methods for increasing internal efficiency of its operation. …”
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Development of a High-Cell-Density Production Process for a Biotherapeutic Yeast, <i>Saccharomyces cerevisiae</i> var. <i>boulardii</i>, for Use as a Human Probiotic by Ghaneshree Moonsamy, Sarisha Singh, Yrielle Roets-Dlamini, Koketso Kenneth Baikgaki, Santosh Omrajah Ramchuran

“…Once the optimised batch was validated in the replicate batches, the statistical analysis indicated a high level of reproducibility, with low variability across key performance indicators such as biomass concentration (unit), CFU production (CFU.mL⁻¹), and substrate utilization efficiency (g.g⁻¹). …”
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Optimization Study of PVT Coupled Water Loop Heat Pump Energy Supply System by Lv Tiangang, Liu Bing, Wu Jun, Zhu Li, Hou Jingxuan

“…By employing the Hooke-Jeeves algorithm, the system's design and operation parameters were optimized with annual cost and system COP as objective functions. Design variables included PVT inclination, azimuth, area, heat pump capacity, and tank volume, while operational variables were PVT backplate temperature and tank temperature. …”
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Optimization of K-Shaped Metal Sealing Ring for Subsea Tubing Hanger Based on Response Surface Method by Huan Xie, Hongxia Zhang, Yiwei Fan, Liyuan Liu, Wei Zeng

“…To address the issue of low optimization efficiency due to the need for repeated finite element calculations during the optimization process, quadratic response surface models are established for the sealing performance indicators of the K-shaped seal ring, which were then used as the optimization objective functions to enhance the optimization efficiency. …”
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Modeling the contribution of micronekton diel vertical migrations to carbon export in the mesopelagic zone by H. Thibault, F. Ménard, J. Abitbol-Spangaro, J.-C. Poggiale, S. Martini

“…Several metabolic parameters accounted for most of the variability in micronekton biomass, organic carbon production, and transport efficiency, mostly linked to respiration rates and capture efficiency. …”
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Toward generalizable prediction of antibody thermostability using machine learning on sequence and structure features by Ameya Harmalkar, Roshan Rao, Yuxuan Richard Xie, Jonas Honer, Wibke Deisting, Jonas Anlahr, Anja Hoenig, Julia Czwikla, Eva Sienz-Widmann, Doris Rau, Austin J. Rice, Timothy P. Riley, Danqing Li, Hannah B. Catterall, Christine E. Tinberg, Jeffrey J. Gray, Kathy Y. Wei

“…In this work, we show two machine learning approaches – one with pre-trained language models (PTLM) capturing functional effects of sequence variation, and second, a supervised convolutional neural network (CNN) trained with Rosetta energetic features – to better classify thermostable scFv variants from sequence. …”
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Natural Diversity of <i>Crataegus monogyna</i> Jacq. in Northeastern Türkiye Encompassing Morphological, Biochemical, and Molecular Features by Bora Erkek, Mehmet Yaman, Ahmet Sümbül, Serap Demirel, Fatih Demirel, Ömer Faruk Coşkun, Ahmet Say, Barış Eren, Adnan Aydin, Ayten Eroglu

“…The Jaccard similarity coefficient ranged from 0.04 (M9 and M16) to 0.63 (M17 and M3), indicating substantial genetic variability. …”
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Long-term conservation tillage breaks the plough pan and promotes the development of preferential flow by Jinze Han, Jianye Li, Qiang Chen, Xingyi Zhang

“…Macropores and preferential flow critically regulate soil hydrological functions and ecosystem services in agricultural systems. …”
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Developing a machine learning model for fast economic optimization of solar power plants using the hybrid method of firefly and genetic algorithms, case study: optimizing solar the... by Ali Omidkar, Razieh Es'haghian, Hua Song

“…The objective functions were to optimize the exergy efficiency and the heat cost. …”
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Learning compositional sequences with multiple time scales through a hierarchical network of spiking neurons. by Amadeus Maes, Mauricio Barahona, Claudia Clopath

“…The hierarchical model redistributes the variability: it achieves high motif fidelity at the cost of higher variability in the between-motif timings.…”
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RNAtango: Analysing and comparing RNA 3D structures via torsional angles. by Marta Mackowiak, Bartosz Adamczyk, Marta Szachniuk, Tomasz Zok

“…RNA molecules, essential for viruses and living organisms, derive their pivotal functions from intricate 3D structures. To understand these structures, one can analyze torsion and pseudo-torsion angles, which describe rotations around bonds, whether real or virtual, thus capturing the RNA conformational flexibility. …”
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Explainable AI-driven assessment of hydro climatic interactions shaping river discharge dynamics in a monsoonal basin by Prashant Parasar, Akhouri Pramod Krishna

“…The main findings of this study are (1) KAN demonstrated high predictive performance with root mean squared error (RMSE) values ranging from 42.7 to 58.3 m3/s, Nash–Sutcliffe efficiency (NSE) between 0.80 and 0.87, mean absolute error (MAE) between 28.9 to 52.7 and R2 values between 0.84 and 0.90 across stations. (2) SHAP based feature contribution analysis identified Relative humidity (hurs), specific humidity (huss), and temperature (tas) as key predictors, while (pr) showed limited contribution due to spatial inherent inconsistencies in GCM precipitation data. (3) The bootstrapped SHAP distributions highlighted substantial variability in feature importance, particularly for humidity variables, revealing station specific uncertainty patterns in model interpretation. (4) The KAN framework results indicate strong temporal alignment and physical realism, confirming KAN’s robustness in capturing seasonal discharge dynamics and extreme flow events under monsoon influence environments. (5) In this study KAN with SHAP (SHapley additive exPlanations) is implemented for hydrological modeling under monsoon-influenced and data-limited regions such as SRB, offering improved accuracy, functional precision and efficiency compared to traditional models. …”
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Smart Fermentation Technologies: Microbial Process Control in Traditional Fermented Foods by Chong Shin Yee, Nur Asyiqin Zahia-Azizan, Muhamad Hafiz Abd Rahim, Nurul Aqilah Mohd Zaini, Raja Balqis Raja-Razali, Muhammad Ameer Ushidee-Radzi, Zul Ilham, Wan Abd Al Qadr Imad Wan-Mohtar

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Combined analysis of 16S rRNA gene sequencing data reveals core vaginal bacteria across livestock species by Lucille C. Jonas, Lucille C. Jonas, Curtis R. Youngs, Stephan Schmitz-Esser, Stephan Schmitz-Esser

“…Recent publications have uncovered a high degree of variability of the livestock vaginal microbiota, making it difficult to focus functional research on individual microorganisms. …”
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Copula Modeling and Uncertainty Propagation in Field‐Scale Simulation of CO2 Fault Leakage by Per Pettersson, Eirik Keilegavlen, Tor Harald Sandve, Sarah E. Gasda, Sebastian Krumscheid

“…The uncertainty in upscaled flow functions and other uncertain parameters are efficiently propagated to leakage estimates using numerical reservoir simulation of a two‐phase system of CO2 and brine. …”
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Assessment of RBFs Based Meshfree Method for the Vibration Response of FGM Rectangular Plate Using HSDT Model by Manish Srivastava, Jeeoot Singh

“…Radial basis functions (RBFs) with modified radial distance are proposed for vibration analysis of functionally graded materials (FGM) rectangular plates. …”
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Neurocognitive factors of new drone Pilots: Identifying candidates with expert potential by Miguel A. Ramallo-Luna, Sara Gonzalez-Torre, Álvaro Rodríguez-Mora, Gabriel G. de la Torre

“…Identifying the neurocognitive variables that influence the performance of these pilots can optimize selection and training processes. …”
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Neural Network-Based Design of a Buck Zero-Voltage-Switching Quasi-Resonant DC–DC Converter by Nikolay Hinov, Bogdan Gilev

“…The converter is a piecewise linear system mathematically described by Kirchhoff’s laws and represented through switching functions. In this way, a mathematical model is used to generate data on the behavior of the state variables obtained under various design parameters. …”
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