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With the development of IoT technology, more and more IoT devices are connected to the network. Due to the hardware constraints of IoT devices themselves, it is difficult for developers to embed security software into them. Therefore, it is better to protect IoT devices at the traffic level. The effect of malicious traffic detection based on neural networks is promising. Still, the slow computation brings some difficulties to deploying AI-based detection systems on edge servers. Time Convolutional Network (TCN) is a high-speed neural network suitable for massively parallel computation. In this paper, we propose Multi-class S-TCN, an improved network supporting multiple classifications based on TCN for the practical needs of IoT scenarios. Besides, we implement a complete IoT traffic security detection procedure based on deep packet inspection and protocol analysis. The proposed Multi-class S-TCN significantly improves the detection speed without degrading the detection effect. Experiments show that this work has better detection performance and faster detection speed compared to existing approaches, proving the effectiveness of the proposed detection flow and Multi-class S-TCN in IoT scenarios. [ABSTRACT FROM AUTHOR]

Using a newly developed particle swarm optimisation technique on crystal structural prediction, we have predicted an orthorhombicImm2 structure for TcN crystal, which is energetically much superior to the previously proposed NbO-type andR-3mstructures. The new phase is stable against decomposition into the mixture of Tc and N at ambient condition. The stability is confirmed by the subsequent calculations on the phonon dispersion curves and elastic constants. An analysis of the mechanical properties indicates thatImm2-TcN is incompressible and common hard material. The evidence of strong covalent bonding of Tc-N, which plays a leading role to form a hard material, is manifested by the partial densities of state analysis. In addition, the thermodynamic properties, such as Debye temperature, heat capacity, thermal expansion coefficient, and Grüneisen parameter of TcN are investigated by the quasi-harmonic Debye model. [ABSTRACT FROM PUBLISHER]

We describe an efficient total synthesis of triciribine, a tricyclic nucleoside with antineoplastic and antiviral properties, starting from 4-amino-6-bromo-5-cyanopyrrolo[2,3-d]pyrimidine. [ABSTRACT FROM AUTHOR]