Fire disaster is one of the most common hazards that threaten public safety and social development: how to improve the fire escape and rescue capacity remains a huge challenge. Here, a 3D honeycomb‐structured woven fabric triboelectric nanogenerator (F‐TENG) based on a flame‐retardant wrapping yarn is developed. The wrapping yarn is fabricated through a continuous hollow spindle fancy twister technology, which is compatible with traditional textile production processes. The resulting 3D F‐TENG can be used in smart carpets as a self‐powered escape and rescue system that can precisely locate the survivor position and point out the escape route to timely assist victim search and rescuing. As interior decoration, the unique design of the honeycomb weaving structure endows the F‐TENG fabric with an excellent noise‐reduction ability. In addition, combining with its good machine washability, air permeability, flame‐retardency, durability, and repeatability features, the 3D F‐TENG may have great potential applications in fire rescue and wearable sensors as well as smart home decoration.

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To investigate the abnormal brain activities in the early stage of Parkinson's disease (PD), the electroencephalogram (EEG) signals were recorded with 20 channels from non-dementia PD patients (18 patients, 8 females) and age matched healthy controls (18 subjects, 8 females) during the resting state. Two methods based on the ordinal patterns of the recorded series, i.e., permutation entropy (PE) and order index (OI), were introduced to characterize the complexity of the cortical activities for two groups. It was observed that the resting-state EEG of PD patients showed lower PE and higher OI than healthy controls, which indicated that the early-stage PD caused the reduced complexity of EEG. We further applied two methods to determine the complexity of EEG rhythms in five sub-bands. The results showed that the gamma, beta and alpha rhythms of PD patients were characterized by lower PE and higher OI, i.e., reduced complexity, than healthy subjects. No significant differences were observed in theta or delta rhythms between two groups. The findings suggested that PE and OI were promising methods to detect the abnormal changes in the dynamics of EEG signals associated with early-stage PD. Further, such changes in EEG complexity may be the early markers of the cortical or subcortical dysfunction caused by PD.

Autonomous aerial refueling autopilot design is addressed in this paper using a novel L 1 neural-network-based adaptive control approach, which is capable of accommodating trailing-vortex-induced uncertainties and uncertainties in control effectiveness. The main advantage of the new approach is its ability of fast adaptation that leads to uniform transient performance for the system's signals, both inputs and outputs, simultaneously, with guaranteed performance specifications. Simulation results verify the benefit of this new approach. Nomenclature c = wing mean aerodynamic chord g = gravity coefficient h = vertical separation from the tanker, positive down I yy = moment of inertia L p = roll moment derivative due to roll rate L r = roll moment derivative due to yaw rate L = roll moment derivative due to side-slip angle L = roll moment derivative due to aileron deflection l = change of the relative horizontal separation, positive forward M = Mach number M q = pitch moment derivative due to pitch angle M = pitch moment derivative due to angle of attack M e = pitch moment derivative due to elevator deflection m = mass N p = yaw moment derivative due to roll rate N r = yaw moment derivative due to yaw rate N = yaw moment derivative due to side slip N r = yaw moment derivative due to rudder deflection N = yaw moment derivative due to aileron deflection p = roll rate q = pitch rate S = wing reference area V = velocity X q = drag derivative due to pitch rate X V = drag derivative due to velocity X = drag derivative due to angle of attack X T = thrust derivative Y = lateral force derivative due to side-slip angle y = lateral separation relative to the tanker, positive right Z = vertical force derivative due to angle of attack = angle of attack, rad = side-slip angle, rad = flight path angle, rad e = elevator deflection, deg r = rudder deflection, deg T = throttle setting a = aileron deflection, deg = density of air, slugs=ft 3 = pitch angle, rad = roll angle, rad

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