From Nasion to Sellion: repositioning landmarks for radioprotection-tailored 3D cephalometric analysis by Marco Serafin, Benedetta Baldini, Elisa Boccalari, Salvatore Bocchieri, Sergio Sambataro, Chiarella Sforza, Giuseppe Baselli, Gianluca Martino Tartaglia, Alberto Caprioglio

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Soil moisture and precipitation intensity jointly control the transit time distribution of quick flow in a flashy headwater catchment by H. Türk, C. Stumpp, M. Hrachowitz, K. Schulz, P. Strauss, G. Blöschl, M. Stockinger

“…The results showed that accounting for both soil moisture and precipitation intensity to define the shape of SAS functions for preferential flow improved the tracer simulation in streamflow (increasing the Nash–Sutcliffe efficiency from 0.31 to 0.51). …”
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Approximate analytical solution of a class of highly nonlinear time–fractional-order partial differential equations by Richard Olu Awonusika

“…The method assumes a fractional power series in the time variable whose expansion coefficients are functions of the space variable. …”
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Three-dimensional dynamics of mesothelin-targeted CAR.CIK lymphocytes against ovarian cancer peritoneal carcinomatosis by Federica Galvagno, Valeria Leuci, Annamaria Massa, Chiara Donini, Ramona Rotolo, Sonia Capellero, Alessia Proment, Letizia Vitali, Andrea Maria Lombardi, Valentina Tuninetti, Lorenzo D’Ambrosio, Alessandra Merlini, Elisa Vigna, Giorgio Valabrega, Luca Primo, Alberto Puliafito, Dario Sangiolo

“…MSLN-CAR.CIK effectively killed and were functionally efficient against OC targets. In a “floating-like” 3D context with floating OC spheroids, both tumor localization and killing by MSLN-CAR.CIK were significantly boosted by fluid flow. …”
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Integrated neural network framework for multi-object detection and recognition using UAV imagery by Mohammed Alshehri, Tingting Xue, Tingting Xue, Ghulam Mujtaba, Yahya AlQahtani, Nouf Abdullah Almujally, Ahmad Jalal, Ahmad Jalal, Hui Liu, Hui Liu, Hui Liu

“…In the end, using an attention function, Vision Transformer-based models classify vehicles seen from above. …”
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PGTransNet: a physics-guided transformer network for 3D ocean temperature and salinity predicting in tropical Pacific by Song Wu, Senliang Bao, Wei Dong, Senzhang Wang, Xiaojiang Zhang, Chengcheng Shao, Junxing Zhu, Xiaoyong Li

“…Moreover, as observed from the spatial distribution of the anomaly correlation coefficient, the model exhibits higher forecasting accuracy for coastal and marginal sea regions.…”
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Investigation into the monitoring and control of mechanical dynamics in inclined mining equipment utilizing digital twin technology by Panshi XIE, Hang YANG, Yongping WU, Baofa HUANG, Weidian LIN, Leilei YI

“…Ultimately, the feasibility and efficacy of this system are corroborated through a multi-functional, variable-angle large-scale "support-surrounding rock" system physical simulation platform. …”
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An updated non-intrusive, multi-scale, and flexible coupling interface in WRF 4.6.0 by S. Masson, S. Jullien, E. Maisonnave, D. Gill, G. Samson, M. Le Corre, L. Renault

“…The present paper details the development and the functionalities of the coupling interface we implemented in WRF. …”
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Enhanced prediction of heating value of municipal solid waste using hybrid neuro-fuzzy model and decision tree-based feature importance assessment by Oluwatobi Adeleke, Obafemi O. Olatunji, Tien-Chien Jen, Iretioluwa Olawuyi

“…To this end, the feature importance analysis of MSW input variables was carried out using the decision tree regressor with the Gini importance (GI) metrics to identify the most influential variable. …”
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Estimation of Above-Ground Biomass for <italic>Dendrocalamus Giganteus</italic> Utilizing Spaceborne LiDAR GEDI Data by Huanfen Yang, Zhen Qin, Qingtai Shu, Li Xu, Jinge Yu, Shaolong Luo, Zaikun Wu, Cuifen Xia, Zhengdao Yang

“…The outcomes reveal that 1) the results showed that the power function emerged as the most efficacious model, with coefficient of determination (<italic>R</italic>²) &#x003D; 0.87 and root mean square error (RMSE) &#x003D; 0.00051 Mg, in estimating the AGB of <italic>Dendrocalamus giganteus</italic>. 2) Based on the feature importance ranking of Random Forest, five variables were selected from the 40 extracted from GEDI, achieving RMSE &#x003D; 8.21 Mg&#x002F;ha and mean absolute error (MAE) &#x003D; 6.12 Mg&#x002F;ha. …”
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Importance Analysis of Vegetation Change Factors in East Africa Based on Machine Learning by Zhang Xiumei, Ma Bo, Zhang Yijie

“…Coefficient of determination (R2), mean absolute error (MAE), and mean relative error (MRE) were used as error indicators to evaluate the potential of the six machine learning algorithms for predicting NDVI changes. …”
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Preoperative Anteroposterior and Lateral Assessment of Sagittal Spinopelvic Parameters Show High Positional Correlation and Measurement Reliability Preceding Both Hip Preservation... by Benjamin D. Kuhns, M.D., M.S., Tyler R. McCarroll, M.D., Roger Quesada-Jimenez, M.D., Ady H. Kahana-Rojkind, M.D., Drashti Sikligar, M.Eng., Meredith F. Cohen, B.A., Benjamin G. Domb, M.D.

“…Interobserver reliability for each measure was evaluated through the intraclass correlation coefficient (ICC). Bivariate linear correlations between AP and lateral standing, supine, and sitting images were obtained. …”
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Revisiting the Group Classification of the General Nonlinear Heat Equation <i>u_t</i> = (<i>K</i>(<i>u</i>)<i>u_x</i>)<i>_x</i> by Winter Sinkala

“…In this paper, we revisit the group classification of the general nonlinear heat (or diffusion) equation <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>u</mi><mi>t</mi></msub><mo>=</mo><msub><mfenced separators="" open="(" close=")"><mi>K</mi><mrow><mo>(</mo><mi>u</mi><mo>)</mo></mrow><mspace width="0.166667em"></mspace><msub><mi>u</mi><mi>x</mi></msub></mfenced><mi>x</mi></msub><mo>,</mo></mrow></semantics></math></inline-formula> where <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>K</mi><mo>(</mo><mi>u</mi><mo>)</mo></mrow></semantics></math></inline-formula> is a non-constant function of the dependent variable. We present the group classification framework, derive the determining equations for the coefficients of the infinitesimal generators of the admitted symmetry groups, and systematically solve for admissible forms of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>K</mi><mo>(</mo><mi>u</mi><mo>)</mo></mrow></semantics></math></inline-formula>. …”
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Effects of Different Irrigation Regimes on Root Growth and Physiological Characteristics of Mulch-Free Cotton in Southern Xinjiang by Feiyan Su, Ziyang Guo, Bingrong Wu, Jichuan Wang, Shuangrong Chen

“…It can be concluded that no mulching has a certain impact on cotton root distribution and leaf physiological function. When the irrigation amount is 450–525 mm and irrigation times is 10–12, it is beneficial for promoting root growth and plays a role in leaf physiological function, and the water use efficiency (WUE) is high, which can provide reference for the scientific water management of mulch-free cotton in production practice.…”
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Sensory profiles in older adults with orthopedic conditions during quiet stance: a cross-sectional study by Marine Brika, France Mourey, Alexandre Kubicki

“…Methods Fifty-one older adults (76.9 ± 7.6 years) were divided into 2 Functional Groups (FG-/FG+) according to a composite score that included 3 variables (gait speed, grip strength and fear of falling). …”
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Analysis of Mechanical and Thermal Material Characteristics of GPL-Reinforced Double-FG Composite Nanoplates under Temperature Load by Kerim Gökhan Aktaş

“…The analysis is conducted to evaluate the influence of variables like temperature rise, GPLs weight ratio and GPLs distribution patterns on the thermal and mechanical properties of the nanoplate such as effective modulus of elasticity, Poisson's ratio, coefficient of thermal expansion and coefficient of thermal conductivity. …”
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MAGNETOHYDRODYNAMICS NANOFERRO FLUID FLOWS PASSING THROUGH A MAGNETIC POROUS SPHERE UNDER THERMAL RADIATION EFFECT by Basuki Widodo, Eirene Juwita Ningtyas Pamela, Dieky Adzkiya, Chairul Imron, Tri Rahayuningsih

“…The dimensional mathematical model is further transformed into non-dimensional mathematical model by using non-dimensional variables. The non-dimensional mathematical model is simplified using the similarity equation by utilizing the stream function. …”
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Implications of thermal stratification and radiative heat flux in blood-based ternary and dihybrid nanomaterial flow through a stretchable cylinder by Muzher Saleem, Ghada A. Khouqeer, Fazal Haq, Naglaa AbdelAll, Arshad Hussain, Mohammed Sallah

“…Non-dimensional mathematical model representing the physical phenomenon is solved through NDSolve function of Mathematica. Behavior of micropolar THNF and HNF velocity and thermal field versus influential variables are investigated. …”
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Flexible Reconfiguration for Optimal Operation of Distribution Network Under Renewable Generation and Load Uncertainty by Behzad Esmaeilnezhad, Hossein Amini, Reza Noroozian, Saeid Jalilzadeh

“…Minimizing the operational costs is difficult when there is a high penetration of renewable resources and variability of loads, which introduces uncertainty. …”
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Load frequency control in isolated island city microgrids using deep graph reinforcement learning considering extensive scenarios by Ping He, Xiongwei Huang, Ruobing He, Linkun Yuan

“…Demonstrated effectively in China Southern Grid’s island microgrid setup, LE-LFC emerges as an advanced solution for modern grid variability, offering superior robustness, adaptability, and learning speed, thus enabling flexible and efficient energy system management.…”
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