Spin-filtering effect in GaAsN: electron-nuclear spin dynamics of Ga<Superscript>3+</Superscript> centers

The impact of Ga³⁺ centers in the spin-filtering effect observed in GaAsN samples is investigated through a model based on the master equation approach. Our results, compared with experimental data, show that, Ga³⁺ are essential to understanding the behavior of the photoluminescence intensity and degree of circular polarization as functions of a Faraday configuration magnetic field. The model presented here takes into account the interplay of Ga²⁺ and Ga³⁺ centers, Zeeman and hyperfine interaction. The various processes that drive the spin-filtering effect, as the spin selective capture of conduction band electrons into Ga centers are also considered here.     

The Bulk Osteosarcoma and Osteosarcoma Stem Cell Activity of a Necroptosis-Inducing Nickel(II)–Phenanthroline Complex

We report the anti-osteosarcoma and anti-osteosarcoma stem cell (OSC) properties of a nickel(II) complex, 1 . Complex 1 displays similar potency towards bulk osteosarcoma cells and OSCs, in the micromolar range. Notably, 1 displays similar or better OSC potency than the clinically approved platinum(II) anticancer drugs cisplatin and carboplatin in two- and three-dimensional osteosarcoma cell cultures. Mechanistic studies revealed that 1 induces osteosarcoma cell death by necroptosis, an ordered form of necrosis. The nickel(II) complex, 1 triggers necrosome-dependent mitrochondrial membrane depolarisation and propidium iodide uptake. Interestingly, 1 does not evoke necroptosis by elevating intracellular reactive oxygen species (ROS) or hyperactivation of poly ADP ribose polymerase (PARP-1). ROS elevation and PARP-1 activity are traits that have been observed for established necroptosis inducers such as shikonin, TRAIL and glutamate. Thus the necroptosis pathway evoked by 1 is distinct. To the best of our knowledge, this is the first report into the anti-osteosarcoma and anti-OSC properties of a nickel complex.     

An evidential approach for detection of abnormal behaviour in the presence of unreliable sensors

We address the problem of abnormal behaviour recognition of the inhabitant of a smart home in the presence of unreliable sensors. The corner stone of this work is a two-level architecture sensor fusion based on the Transferable Belief Model (TBM). The novelty of our work lies in the way we detect both unreliable sensors and abnormal behaviour within our architecture by using a temporal analysis of conflict resulting from the fusion of sensors. Detection of abnormal behaviour is based on a prediction/observation process and the influence of the faulty sources is discarded by discounting coefficients. Our architecture is tested in a real-life setting using three heterogeneous sensors enabling the detection of impossible transitions between three possible postures: Sitting, Standing and Lying. The impact of having a faulty sensor management is also tested in the real-life experiment for posture detection.