Background: Drug repositioning is a new research area in drug development. It aims to discover novel therapeutic uses of existing drugs. It could accelerate the process of designing novel drugs for some diseases and considerably decrease the cost. The traditional method to determine novel therapeutic uses of an existing drug is quite laborious. It is alternative to design computational methods to overcome such defect. Objective: This study aims to propose a novel model for the identification of drug–disease associations. Method: Twelve drug networks and three disease networks were built, which were fed into a powerful network-embedding algorithm called Mashup to produce informative drug and disease features. These features were combined to represent each drug–disease association. Classic classification algorithm, random forest, was used to build the model. Results: Tenfold cross-validation results indicated that the MCC, AUROC, and AUPR were 0.7156, 0.9280, and 0.9191, respectively. Conclusion: The proposed model showed good performance. Some tests indicated that a small dimension of drug features and a large dimension of disease features were beneficial for constructing the model. Moreover, the model was quite robust even if some drug or disease properties were not available.

Ti ion and C ion is implanted into AZ31 magnesium alloy surface by metal vapor vacuum arc (MEVVA) implanter operating with a modified cathode. This metal arc ion source has a broad beam and high current capabilities. Implantation energy is fixed at 45K eV and dose is 9×1017 cm-2 and 3×1017 cm-2 respectively. Through ion implantation, Ti ion implantation layer approximately 1000nm thick is directly formed on the surface of AZ31 magnesium alloy, by which its surface property is greatly improved. Microstructure, the component distribution and phase composition are analyzed using scanning electron microscopy (SEM) and X-ray diffraction (XRD). The property of hardness of the ion implantation layer was studied by HMV-1T Vickers micro hardness tester. The results show that Ti ion implantation layer of a magnesium alloy surface is mainly composed of TiO2, MgO and a little of TiO. The Ti-C double ions implantation layer is composed of MgO, TiC. The hardness of ion implantation layer is improved.

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Different thickness of CdZnTe films were deposited onto glass substrates by RF magnetron sputtering from Cd0.9Zn0.1Te crystals target. Their structural characteristics were studied by X-ray diffraction (XRD). The XRD experiments showed that the films are polycrystalline and have a zinc-blende (cubic) structure. The crystallite size and micro-strain were calculated. It is observed that the crystallite size increases and micro-strain decreases with the film thickness. The optical measurements showed that the average transmittance of all the samples have is less than 50% in the visible range. The possible optical transition in these films is found to be allowed direct transition with energy gap increase from 1.53 to 1.75 eV. For the electrical properties, the sheet resistivity decreased from 2.582×108 to3.069×107 Ohm/sq when the thickness increased from 307 to 823 nm; while the carrier concentration seems to be less affected by the film thickness. This behaviour in electrical properties was explained by the crystallinity and the grain size evolution.

With the application and popularization of the Internet of Things (IoT), while the IoT devices bring us intelligence and convenience, the privacy protection issue has gradually attracted people’s attention. Access control technology is one of the important methods to protect privacy. However, the existing IoT access control technologies have extensive problems such as coarse-grainedness, weak auditability, lack of access process control, and excessive privileges, which make the security and privacy of our IoT devices face great threats. Based on this, a blockchain-based and encrypted currency-based access control model CcBAC supported by Trusted Execution Environment (TEE) technology is proposed, which can provide fine-graininess, strong auditability, and access procedure control for the Internet of Things. In this study, the technical principle, characteristics, and research status of the control model are introduced, and the framework of the CcBAC model is expounded in detail and formally defined. Moreover, the functions in the model are described in detail, and a specific access control process in general scenarios is presented for the model. Finally, the practicability of this model is verified through theoretical analysis and experimental evaluation, which proves that this model not only enables resource owners to fully control the access to their resources, but also takes into account the fine-graininess and auditable access control.