Ionic and electronic properties of the topological insulator Bi2_2Te2_2Se investigated using β\beta-detected nuclear magnetic relaxation and resonance of 8^8Li

We report measurements on the high temperature ionic and low temperature electronic properties of the 3D topological insulator Bi$_2$Te$_2$Se using ion-implanted $^8$Li $\beta$-detected nuclear magnetic relaxation and resonance. With implantation energies in the range 5-28 keV, the probes penetrate beyond the expected range of the topological surface state, but are still within 250 nm of the surface. At temperatures above ~150 K, spin-lattice relaxation measurements reveal isolated $^8$Li$^{+}$ diffusion with an activation energy $E_{A} = 0.185(8)$ eV and attempt frequency $\tau_{0}^{-1} = 8(3) \times 10^{11}$ s$^{-1}$ for atomic site-to-site hopping. At lower temperature, we find a linear Korringa-like relaxation mechanism with a field dependent slope and intercept, which is accompanied by an anomalous field dependence to the resonance shift. We suggest that these may be related to a strong contribution from orbital currents or the magnetic freezeout of charge carriers in this heavily compensated semiconductor, but that conventional theories are unable to account for the extent of the field dependence. Conventional NMR of the stable host nuclei may help elucidate their origin.Comment: 17 pages, 12 figures, submitted to Phys. Rev.

Ion-Implanted 8^8Li Nuclear Magnetic Resonance in Highly Oriented Pyrolytic Graphite

We report $\beta$-detected nuclear magnetic resonance of ultra-dilute $^{8}$Li$^{+}$ implanted in highly oriented pyrolytic graphite (HOPG). The absence of motional narrowing and diffusional spin-lattice relaxation implies Li$^+$ is not appreciably mobile up to 400 K, in sharp contrast to the highly lithiated stage compounds. However, the relaxation is remarkably fast and persists down to cryogenic temperatures. Ruling out extrinsic paramagnetic impurities and intrinsic ferromagnetism, we conclude the relaxation is due to paramagnetic centers correlated with implantation. While the resulting effects are not consistent with a Kondo impurity, they also differ from free paramagnetic centers, and we suggest that a resonant scattering approach may account for much of the observed phenomenology

The Transformation from Traditional Nonprofit Organizations to Social Enterprises: An Institutional Entrepreneurship Perspective

The development of commercial revenue streams allows traditional nonprofit organizations to increase financial certainty in response to the reduction of traditional funding sources and increased competition. In order to capture commercial revenue-generating opportunities, traditional nonprofit organizations need to deliberately transform themselves into social enterprises. Through the theoretical lens of institutional entrepreneurship, we explore the institutional work that supports this transformation by analyzing field interviews with 64 institutional entrepreneurs from UK-based social enterprises. We find that the route to incorporate commercial processes and convert traditional nonprofit organizations into social enterprises requires six distinct kinds of institutional work at three different domains; these are—“engaging commercial revenue strategies”, “creating a professionalized organizational form”, and “legitimating a socio-commercial business model”. In elaborating on social entrepreneurship research and practice, we offer a comprehensive framework delineating the key practices contributing to the transformation from traditional nonprofit organizations to social enterprises. This extends our understanding of the ex-ante strategy of incorporating commercial processes within social organizations. Furthermore, the identification of these practices also offers an important tool for scholars in this field to examine the connection (or disconnection) of each practice with different ethical concerns of social entrepreneurship in greater depth.British Academ

Blind fMRI source unmixing via higher-order tensor decompositions

Background: The growing interest in neuroimaging technologies generates a massive amount of biomedical data of high dimensionality. Tensor-based analysis of brain imaging data has been recognized as an effective analysis that exploits its inherent multi-way nature. In particular, the advantages of tensorial over matrix-based methods have previously been demonstrated in the context of functional magnetic resonance imaging (fMRI) source localization. However, such methods can also become ineffective in realistic challenging scenarios, involving, e.g., strong noise and/or significant overlap among the activated regions. Moreover, they commonly rely on the assumption of an underlying multilinear model generating the data. New method: This paper aims at investigating the possible gains from exploiting the 4-dimensional nature of the brain images, through a higher-order tensorization of the fMRI signal, and the use of less restrictive generative models. In this context, the higher-order block term decomposition (BTD) and the PARAFAC2 tensor models are considered for the first time in fMRI blind source separation. A novel PARAFAC2-like extension of BTD (BTD2) is also proposed, aiming at combining the effectiveness of BTD in handling strong instances of noise and the potential of PARAFAC2 to cope with datasets that do not follow the strict multilinear assumption. Comparison with existing methods: The methods were tested using both synthetic and real data and compared with state of the art methods. Conclusions: The simulation results demonstrate the effectiveness of BTD and BTD2 for challenging scenarios (presence of noise, spatial overlap among activation regions and inter-subject variability in the haemodynamic response function (HRF)). © 2018 Elsevier B.V