The aim was to evaluate the mismatch negativity (MMN) component, a correlate of the automatic detection of changes in the acoustic environment, in healthy adults, and adults with amnestic mild cognitive impairment (aMCI). Forty-three aMCI subjects and 43 healthy Chinese older adults were arranged into experimental group and control group, respectively. Their MMN amplitude and latency were measured at the FZ, FCZ, and CZ electrode sites under a passive auditory oddball task. The results showed that the latencies obtained from the FZ, FCZ, and CZ electrode sites were significantly longer in the aMCI adults than in the control adults (P  < 0.01) while there were no significant differences in MMN amplitude between two groups (P  > 0.05). The MMN latency was found to be a sensitive and specific biomarker of aMCI.

No abstract

With the continuous development of economy, China, as the largest agricultural country in the world, has a low level of agricultural automation and a large demand for labor. Therefore, it is necessary to improve production efficiency and improve the environment by developing smart agriculture, so as to realize the dual benefits of agriculture and environment. The traditional CPU and single chip microcomputer have weak running speed and timing implementation ability. In this paper, a design and implementation scheme of intelligent agricultural soil acquisition system based on FPGA is proposed by investigating the research status and development trend of a large number of domestic and foreign intelligent orchards. It has the advantages of high integration, fast speed, strong reliability and low power consumption. This paper proposes the overall design scheme of the system. The hardware part includes the selection of various devices, and the software part includes the language, software development and simulation. It mainly includes soil information collection, data transmission, data storage, data processing and other aspects, which simplifies the design of the circuit and conforms to the development trend of modern intelligent orchard.

The operation and inspection of external damage of power grid is becoming more and more difficult, mainly reflected in the uncertainty of risk and insufficient manpower. At present, most of the on-site inspection rely on human inspection since new technology cannot respond to unexpected situations. In this paper, we proposed a social mobilized inspection system. By mobilized the social forces around power facilities, we propose an inspection framework to encourage people upload photos of external damage. To ensure the incentive system transparency, we use block chain technology as the decentralized database. This method provides a new insight against external damage of power grid and is hopefully to be used in inspection system.

This paper describes the design of parameter dependent robust model predictive controller (PD-RMPC) for a class of flexible air-breathing hypersonic vehicles. The strong system uncertainties, high nonlinearity, strong coupling, input saturation and flight state constraints are challenging problems in the design of control system. Therefore, a control method that can handle model uncertainties and perturbations while adhering to strict flight constraints is necessary. The nonlinear dynamic model with aerothermoelastic mode is transformed into linear parameter varying (LPV) model, and then Tensor-Product model transformation technology is applied to obtain the convex hull representations of LPV model. Based on linear matrix inequalities (LMIs), a novel parameter dependent robust model predictive control algorithm by are presented for the LPV model with input saturation and state constraints. The proposed control strategy not only addresses the issue of stability robustness with respect to parametric model uncertainty and aerothermoelastic mode, but also explicitly deals with system constraints and guarantees the control and state are within their limits. Finally, the numerical simulation results proved availability of the proposed method.