The spectral and transport properties of strongly correlated metals, such asSrVO$_3$ (SVO), are widely attributed to electron-electron ($e$-$e$)interactions, with lattice vibrations (phonons) playing a secondary role. Here,using first-principles electron-phonon ($e$-ph) and dynamical mean field theorycalculations, we show that $e$-ph interactions play an essential role in SVO:they govern the electron scattering and resistivity in a wide temperature rangeabove 30 K, and induce an experimentally observed kink in the spectralfunction. In contrast, the $e$-$e$ interactions control quasiparticlerenormalizations and low temperature transport, and enhance the $e$-phcoupling. We clarify the origin of the near $T^2$ temperature dependence of theresistivity by analyzing the $e$-$e$ and $e$-ph limited transport regimes. Ourwork disentangles the electronic and lattice degrees of freedom in aprototypical correlated metal, revealing the dominant role of $e$-phinteractions in SVO.
Brain age estimation has emerged as a crucial biomarker for quantifying inter-individual variability in brain aging and identifying risks of cognitive decline. This is particularly relevant for the study of neurodegenerative conditions like Alzheimer’s disease, where deviations from normal brain aging patterns can serve as early indicators of pathology. We introduce an interpretable framework for brain age estimation that adopts a multi-region perspective to capture heterogeneous neuroanatomical changes. Groupwise registration was employed to construct sex- and age-stratified templates, enabling the computation of anatomically meaningful displacement vector fields (DVFs) that characterize voxel-wise structural deviations from the population average. From these DVFs, features were extracted in fifteen brain regions using a 3D shape context descriptor to encode displacement direction and magnitude. Validation was performed on 1,956 T1-weighted MRI scans from cognitively normal individuals in the ADNI dataset (ages 60–90). The combined multi-region model achieved a mean absolute error (MAE) of 1.66 ± 0.15 years ( R 2 = 0.84 ± 0.05) for males and 1.81 ± 0.12 years ( R 2 = 0.80 ± 0.04) for females, significantly outperforming many contemporary deep learning models. These findings demonstrate that biologically interpretable, registration-derived features—when analyzed from a multi-regional perspective—can yield robust and accurate estimates of brain age. Beyond predictive accuracy, the framework provides insights into the regional specificity of aging processes, thereby offering a foundation for early detection strategies and targeted clinical applications in neurodegenerative disease research.
Millimeter-wave and sub-THz wireless communications promise high data rate and low-latency transmission for both indoor and outdoor short-range applications, but their deployment faces challenges due to the high isotropic path loss and severe obstacle penetration attenuation. The upper mid-band -also known as "FR3", between 7 and 24 GHz -is gaining significant attention for 6G applications, but the corresponding propagation and material characteristics still remain scarcely investigated. Therefore, thorough studies of radio-wave interaction with the most common construction materials in the cited frequency bands are very important for the design and deployment of next-generation wireless systems. The present study investigates the attenuation and scattering behaviors of some of the most common construction materials at frequencies ranging from 10 to 153 GHz, using proper measurement setups and post-processing procedures. Our findings can contribute to the design of future communication systems and to the calibration of propagation simulators that are necessary for their optimization and deployment in real-life scenarios.
Traditional structural tests are powerful automatic approaches for capturing faulty behavior in integrated circuits. Besides the ease of generating test patterns, structural methods are known to be able to cover a vast but incomplete spectrum of all possible faults in a System-on-Chip (SoC). A new step in the manufacturing test flow has been added to fill the leftover gaps of structural tests, called the System-Level Test (SLT), which resembles the final workload, and environment. This work illustrates how to build up an automated generation engine to synthesize SLT programs that effectively attack structural test weaknesses from both a holistic and an analytical perspective. The methodology targets the crossbar module, as one of the most critical areas in the SoC, and it simultaneously creates a ripple effect across the un-core logic. Experimental results are conducted on an automotive SoC manufactured by STMicroelectronics.