A Method for Recognizing Fatigue Driving Based on Dempster-Shafer Theory and Fuzzy Neural Network

This study proposes a method based on Dempster-Shafer theory (DST) and fuzzy neural network (FNN) to improve the reliability of recognizing fatigue driving. This method measures driving states using multifeature fusion. First, FNN is introduced to obtain the basic probability assignment (BPA) of each piece of evidence given the lack of a general solution to the definition of BPA function. Second, a modified algorithm that revises conflict evidence is proposed to reduce unreasonable fusion results when unreliable information exists. Finally, the recognition result is given according to the combination of revised evidence based on Dempster’s rule. Experiment results demonstrate that the recognition method proposed in this paper can obtain reasonable results with the combination of information given by multiple features. The proposed method can also effectively and accurately describe driving states

Speed Control Based on ESO for the Pitching Axis of Satellite Cameras

The pitching axis is the main axis of a satellite camera and is used to control the pitch posture of satellite cameras. A control strategy based on extended state observer (ESO) is designed to obtain a fast response speed and highly accurate pitching axis control system and eliminate disturbances during the adjustment of pitch posture. First, a sufficient condition of stabilization for ESO is obtained by analyzing the steady-state error of the system under step input. Parameter tuning and disturbance compensation are performed by ESO. Second, the ESO of speed loop is designed by the speed equation of the pitching axis of satellite cameras. The ESO parameters are obtained by pole assignment. By ESO, the original state variable observes the motor angular speed and the extended state variable observes the load torque. Therefore, the external load disturbances of the control system are estimated in real time. Finally, simulation experiments are performed for the system on the cases of nonload starting, adding external disturbances on the system suddenly, and the load of system changing suddenly. Simulation results show that the control strategy based on ESO has better stability, adaptability, and robustness than the PI control strategy

Effect of Heat Processing on the Functional Properties of Myosin in Three Kinds of Hairtail

Changes in the functional properties of myosin and the tissue microstructure of hooked, trawl-netted, and radar-netted hairtail (Trichiurus haumela) were investigated under different heating temperatures. Hairtails were water bathed at 30, 50, 70 or 90 ℃ and evaluated for cooking loss and water-holding capacity (WHC) as well as myosin turbidity, solubility, emulsifying capacity, foaming capacity and foam stability, and carbonyl content after 10 min. Besides, hematoxylin-eosin (HE) staining was used to analyze the effects of different heating temperatures on the tissue microstructure of hairtails. The results showed that as the heating temperature rose, the cooking loss and water-holding capacity of muscle decreased gradually for the three kinds of hairtail. Myosin turbidity and carbonyl content increased, and solubility, emulsifying activity index (EAI) and emulsion stability index (ESI), foaming capacity and foam stability decreased continuously. The decrease in muscle WHC and myosin solubility and the increase in myosin turbidity were all smaller in radar-netted hairtails than in the two other kinds. In addition, the HE staining results showed that with increasing heating temperature, the space between muscle fiber bundles in muscle tissues increased for all kinds of hairtail, and different degrees of breakage occurred. When the heating temperature was 50 ℃, the structure of collagen and muscle fibers was the most complete in the muscle tissue of radar-netted hairtail. Summarily, the muscle quality of all three kinds of hairtail decreased with the increase in heating temperature, and the muscle quality of radar-netted hairtail was the most stable

Periplasmic biomineralization for semi-artificial photosynthesis

Semiconductor-based biointerfaces are typically established either on the surface of the plasma membrane or within the cytoplasm. In Gram-negative bacteria, the periplasmic space, characterized by its confinement and the presence of numerous enzymes and peptidoglycans, offers additional opportunities for biomineralization, allowing for nongenetic modulation interfaces. We demonstrate semiconductor nanocluster precipitation containing single- and multiple-metal elements within the periplasm, as observed through various electron- and x-ray-based imaging techniques. The periplasmic semiconductors are metastable and display defect-dominant fluorescent properties. Unexpectedly, the defect-rich (i.e., the low-grade) semiconductor nanoclusters produced in situ can still increase adenosine triphosphate levels and malate production when coupled with photosensitization. We expand the sustainability levels of the biohybrid system to include reducing heavy metals at the primary level, building living bioreactors at the secondary level, and creating semi-artificial photosynthesis at the tertiary level. The biomineralization-enabled periplasmic biohybrids have the potential to serve as defect-tolerant platforms for diverse sustainable applications

Phytoremediation Potential of Three Species of Macrophytes for Nitrate in Contaminated Water

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