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Abstract We report a transport study on Pd₃In₇which displays multiple Dirac type-II nodes in its electronic dispersion. Pd₃In₇is characterized by low residual resistivities and high mobilities, which are consistent with Dirac-like quasiparticles. For an applied magnetic field (μ₀H) having a non-zero component along the electrical current, we find a large, positive, and linear inμ₀Hlongitudinal magnetoresistivity (LMR). The sign of the LMR and its linear dependence deviate from the behavior reported for the chiral-anomaly-driven LMR in Weyl semimetals. Interestingly, such anomalous LMR is consistent with predictions for the role of the anomaly in type-II Weyl semimetals. In contrast, the transverse or conventional magnetoresistivity (CMR for electric fieldsE⊥μ₀H) is large and positive, increasing by 10³−10⁴% as a function ofμ₀Hwhile following an anomalous, angle-dependent power law$${\rho }_{{{{\rm{xx}}}}}\propto {({\mu }_{0}H)}^{n}$$ ${\rho }_{\mathrm{xx}}\propto {\left({\mu }_{0}H\right)}^n$withn(θ) ≤ 1. The order of magnitude of the CMR, and its anomalous power-law, is explained in terms of uncompensated electron and hole-like Fermi surfaces characterized by anisotropic carrier scattering likely due to the lack of Lorentz invariance. 

We describe interfaces and visualizations in the CRAIVE (Collaborative Research Augmented Immersive Virtual Environment) Lab, an interactive human scale immersive environment at Rensselaer Polytechnic Institute. We describe the physical infrastructure and software architecture of the CRAIVE-Lab, and present two immersive scenarios within it. The first is “person following”, which allows a person walking inside the immersive space to be tracked by simple objects on the screen. This was implemented as a proof of concept of the overall system, which includes visual tracking from an overhead array of cameras, communication of the tracking results, and large-scale projection and visualization. The second “smart presentation” scenario features multimedia on the screen that reacts to the position of a person walking around the environment by playing or pausing automatically, and additionally supports real-time speech-to-text transcription. Our goal is to continue research in natural human interactions in this large environment, without requiring user-worn devices for tracking or speech recording.