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Communication between connected objects in the Internet of Things (IoT) often requires secure and reliable authentication mechanisms to verify identities of entities and prevent unauthorized access to sensitive data and resources. Unlike other domains, IoT offers several advantages and opportunities, such as the ability to collect real-time data through numerous sensors. These data contains valuable information about the environment and other objects that, if used, can significantly enhance authentication processes. In this paper, we propose a novel idea to building opportunistic sensor-based authentication factors by leveraging existing IoT sensors in a system of systems approach. The objective is to highlight the promising prospects of opportunistic authentication factors in enhancing IoT security. We claim that sensors can be utilized to create additional authentication factors, thereby reinforcing existing object-to-object authentication mechanisms. By integrating these opportunistic sensor-based authentication factors into multi-factor authentication schemes, IoT security can be substantially improved. We demonstrate the feasibility and effectivenness of our idea through illustrative experiments in a parking entry scenario, involving both mobile robots and cars, achieving high identification accuracy. We highlight the potential of this novel method to improve IoT security and suggest future research directions for formalizing and comparing our approach with existing techniques.

Deep Reinforcement Learning (DRL) has achieved remarkable success in scenarios such as games and has emerged as a potential solution for control tasks. That is due to its ability to leverage scalability and handle complex dynamics. However, few works have targeted environments grounded in real-world settings. Indeed, real-world scenarios can be challenging, especially when faced with the high dimensionality of the state space and unknown reward function. We release a testbed consisting of an environment simulator and demonstrations of human operation concerning pump scheduling of a real-world water distribution facility to facilitate research. The pump scheduling problem can be viewed as a decision process to decide when to operate pumps to supply water while limiting electricity consumption and meeting system constraints. To provide a starting point, we release a well-documented codebase, present an overview of some challenges that can be addressed and provide a baseline representation of the problem. The code and dataset are available at https://gitlab.com/hdonancio/pumpscheduling.

We study by scanning thermal microscopy the nanoscale thermal conductance of films (40 to 400 nm thick) of [1]benzothieno[3,2-b][1]benzothiophene (BTBT) and 2,7-dioctyl[1]benzothieno[3,2-b][1]benzothiophene (C8-BTBT-C8). We demonstrate that the out-of-plane thermal conductivity is significant along the interlayer direction, larger for BTBT (0.63 +/- 0.12 W m-1 K-1) compared to C8-BTBT-C8 (0.25 +/- 0.13 W m-1 K-1). These results are supported by molecular dynamics calculations (Approach to Equilibrium Molecular Dynamics method) performed on the corresponding molecular crystals. The calculations point to significant thermal conductivity (3D-like) values along the 3 crystalline directions, with anisotropy factors between the crystalline directions below 1.8 for BTBT and below 2.8 for C8-BTBT-C8, in deep contrast with the charge transport properties featuring a two-dimensional character for these materials. In agreement with the experiments, the calculations yield larger values in BTBT compared to C8-BTBT-C8 (0.6-1.3 W m-1 K-1 versus 0.3-0.7 W m-1 K-1, respectively). The weak thickness dependence of the nanoscale thermal resistance is in agreement with a simple analytical model., Comment: Nanoscale (2021)

The luminescence properties of the $\mathrm{[UO_2Cl_4]^{2-}}$ complex in an organic phase, especially the influence of large organic counter cations, have been studied by time-resolved laser-induced fluorescence spectroscopy (TRLFS) and ab initio modeling. The experimental spectrum was assigned by vibronic Franck-Condon calculations on quantum chemical models based on relativistic density functional approaches. The shape of the luminescence spectrum of the uranyl tetrachloride complex is determined by symmetrical vibrations and geometrical change upon emission. The possible change of the luminescence properties depending on the first and second uranyl coordination sphere was predicted theoretically for $\mathrm{[UO_2Br_4]^{2-}}$ and $\mathrm{[R_4N]_2[UO_2Cl_4]}$ ($\mathrm{R_4N}$ = $\mathrm{[Bu_4N]}$, $\mathrm{[{A336}]}$) systems. The computations reveal that for U(VI), the second coordination sphere has little influence on the spectrum shape, making speciation of uranyl complexes with identical first coordination-sphere ligands tedious to discriminate. The computed structural changes agreed well with experimental trends; theoretical spectra and peaks attribution are in a good accordance with TRLFS and magnetic circular dichroism (MCD) data respectively.