Near-infrared spectroscopy analysis to predict urinary allantoin in dairy cows by Leonardo A.C. Ribeiro, Guilherme L. Menezes, Tiago Bresolin, Sebastian I. Arriola Apelo, Joao R.R. Dórea

“…The raw spectra were preprocessed using scatter correlation methods and spectral derivatives. The partial least squares regression model achieved an R2 of 0.55, a concordance correlation coefficient of 0.73, and a root mean squared error of prediction (RMSEP) of 3.63 mmol/L to predict allantoin concentration from the spectra data set without preprocessing. …”
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Inversion Study of Mechanical Parameters of Tunnel Surrounding Rock Based on Similar Test by Xianyun Wang, Hewei Cui, Hailiang Xu, Dong An, Yimin Song

“…Based on similar model tests and finite element simulations, inversion study of the mechanical parameters of the tunnel surrounding rock by combining artificial fish swarm algorithm (AFSA) and digital scattering correlation method is carried out. The inversion of the mechanical parameters of the tunnel surrounding rock is carried out by iterating the optimization algorithm to minimize the objective function value through similar model test with the displacement measurements obtained by the digital scattering correlation method as the known quantity and the nodal displacement simulation values obtained by numerical simulation as the unknown quantity. …”
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RSCIWANet: Regional Spatial-Channel Information Weighted Attention Network for Video SAR and Large-Scale SAR Image Targets Detection by Hao Chang, Ping Lang, Xiongjun Fu, Kunyi Guo, Xinqing Sheng, Jialin Guan, Chuyi Liu

“…Channel self-attention enhances cross-regional interactions to capture target-environment scattering correlations. 2) Boundary-aware loss employs edge overlapping penalties to improve localization of fuzzy shadow edges, with adaptive weighting to amplify small-target gradient contributions during backpropagation. 3) Context-preserving sliding window detection strategy for large-scale images, which can carry out comprehensive and robust detection. …”
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Causal Discovery in Astrophysics: Unraveling Supermassive Black Hole and Galaxy Coevolution by Zehao Jin, Mario Pasquato, Benjamin L. Davis, Tristan Deleu, Yu Luo, Changhyun Cho, Pablo Lemos, Laurence Perreault-Levasseur, Yoshua Bengio, Xi Kang, Andrea Valerio Macciò, Yashar Hezaveh

“…The supermassive black hole (SMBH)–galaxy interaction has long been constrained by observed scaling relations, which is low-scatter correlations between variables such as SMBH mass and the central velocity dispersion of stars in a host galaxy's bulge. …”
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