Pressure-constrained sonication activation of flexible printed metal circuit.

Metal micro/nanoparticle ink-based printed circuits have shown promise for promoting the scalable application of flexible electronics due to enabling superhigh metallic conductivity with cost-effective mass production. However, it is challenging to activate printed metal-particle patterns to approach the intrinsic conductivity without damaging the flexible substrate, especially for high melting-point metals. Here, we report a pressure-constrained sonication activation (PCSA) method of the printed flexible circuits for more than dozens of metal (covering melting points from room temperature to 3422 °C) and even nonmetallic inks, which is integrated with the large-scale roll-to-roll process.

Volume-Metallization 3D-Printed Polymer Composites.

3D printing polymer or metal can achieve complicated structures while lacking multifunctional performance. Combined printing of polymer and metal is desirable and challenging due to their insurmountable mismatch in melting-point temperatures. Here, a novel volume-metallization 3D-printed polymer composite (VMPC) with bicontinuous phases for enabling coupled structure and function, which are prepared by infilling low-melting-point metal (LM) to controllable porous configuration is reported.

Survey of Time Series Data Generation in IoT.

Nowadays, with the rapid growth of the internet of things (IoT), massive amounts of time series data are being generated. Time series data play an important role in scientific and technological research for conducting experiments and studies to obtain solid and convincing results. However, due to privacy restrictions, limited access to time series data is always an obstacle.

CrowdMed-II: a blockchain-based framework for efficient consent management in health data sharing.

The healthcare industry faces serious problems with health data. Firstly, health data is fragmented and its quality needs to be improved. Data fragmentation means that it is difficult to integrate the patient data stored by multiple health service providers.

Automatic approach for constructing a knowledge graph of knee osteoarthritis in Chinese.

In this study, a medical knowledge graph is constructed from the electronic medical record text of knee osteoarthritis patients to support intelligent medical applications such as knowledge retrieval and decision support, and to promote the sharing of medical resources. After constructing the domain ontology of knee osteoarthritis and manually labeling, we trained a machine learning model to automatically perform entity recognition and entity relation extraction, and then used a graph database to construct the knowledge graph of knee osteoarthritis. The experiment proves that the knowledge graph is comprehensive and reliable, and the knowledge graph construction method proposed in this study is effective.

Using Greedy Random Adaptive Procedure to Solve the User Selection Problem in Mobile Crowdsourcing.

With the rapid development of mobile networks and smart terminals, mobile crowdsourcing has aroused the interest of relevant scholars and industries. In this paper, we propose a new solution to the problem of user selection in mobile crowdsourcing system. The existing user selection schemes mainly include: (1) find a subset of users to maximize crowdsourcing quality under a given budget constraint; (2) find a subset of users to minimize cost while meeting minimum crowdsourcing quality requirement.