Superhydrophobic Bulgy Windmill for Synchronous Efficient Fog Collection and Power Generation.

The shortage of freshwater resources is a serious problem faced by mankind in the 21st century. To maximize the acquisition of freshwater resources, numerous fog collectors have been constructed. In the process of fog collection accompanied by the movement of the wind, the mechanical energy brought about by the wind is often ignored. Based on this, inspired by beetles and origami art, we designed a windmill installation with a bump on the edge. Droplets nucleate at the windmill bulge and accelerate the transport process under the action of centrifugal force. This leads to quick fog collection and reduces the secondary evaporation rate of freshwater resources. The fog collection efficiency can reach 2.8 times that of the original sample. Moreover, the windmill can convert mechanical energy into electricity while collecting fog, and the operating voltage of a single windmill can reach 0.85 V. After the array, the amount of fog collected by the windmill and the power generation voltage can be increased by multiple times, which realizes the efficient use of energy and provides a new idea for the design of an efficient fog collector in the future.

Fe-Catalyzed Selective Formal Insertion of Diazo Compounds into C(sp)-C(sp3) Bonds of Propargyl Alcohols: Access to Alkyne-Substituted All-Carbon Quaternary Centers.

The construction of all-carbon quaternary centers, especially those containing an alkyne-substituted framework, represents an important challenge in organic synthesis. Here we present a novel Fe-catalyzed selective formal insertion of diazo compounds into C(sp)-C(sp3) bonds of propargyl alcohols under mild conditions that enables the streamlined construction of alkyne-substituted all-carbon quaternary centers. This unique strategy starts with in situ generation of an ester group in the presence of carboxylic acids, followed by insertion of metal-carbene into C(sp)-C(sp3) bonds, which may open up a new reaction mode for exploring metal-carbene insertion into acyclic C-C bonds.

HKF-SVR Optimized by Krill Herd Algorithm for Coaxial Bearings Performance Degradation Prediction.

In real industrial applications, bearings in pairs or even more are often mounted on the same shaft. So the collected vibration signal is actually a mixed signal from multiple bearings. In this study, a method based on Hybrid Kernel Function-Support Vector Regression (HKF-SVR) whose parameters are optimized by Krill Herd (KH) algorithm was introduced for bearing performance degradation prediction in this situation. First, multi-domain statistical features are extracted from the bearing vibration signals and then fused into sensitive features using Kernel Joint Approximate Diagonalization of Eigen-matrices (KJADE) algorithm which is developed recently by our group. Due to the nonlinear mapping capability of the kernel method and the blind source separation ability of the JADE algorithm, the KJADE could extract latent source features that accurately reflecting the performance degradation from the mixed vibration signal. Then, the between-class and within-class scatters (SS) of the health-stage data sample and the current monitored data sample is calculated as the performance degradation index. Second, the parameters of the HKF-SVR are optimized by the KH (Krill Herd) algorithm to obtain the optimal performance degradation prediction model. Finally, the performance degradation trend of the bearing is predicted using the optimized HKF-SVR. Compared with the traditional methods of Back Propagation Neural Network (BPNN), Extreme Learning Machine (ELM) and traditional SVR, the results show that the proposed method has a better performance. The proposed method has a good application prospect in life prediction of coaxial bearings.

A coefficient-free and continuous blood pressure estimation method based on the arterial lumen area model.

Oscillometry is the most popular technique for automatic blood pressure (BP) estimation. This method relies on recording the cuff deflation curve (CDC) from a high suprasystolic BP (SSBP) to a low subdiastolic BP (SDBP) and is very sensitive to noise caused by breathing, motion artifacts, muscle contraction and the environment. We developed a unified BP estimation method involving two integrated sub-procedures based on the arterial lumen area (ALA) model and applied it for continuous BP measurement. Our proposed method is coefficient free and continuous. No empirical coefficients are applied, and the CDC varies within a low-pressure range of 40-80 mm Hg, which can be sustainably imposed on our wrists. The first sub-procedure estimates the mean arterial pressure (MAP) and arterial compliance parameter b under a complete CDC period. In the second sub-procedure, the systolic BP (SBP) and diastolic BP (DBP) are estimated based on the dynamic-updated oscillometric waveform. We applied this method on 300 continuously oscillometric traces recorded from 20 male and female healthy subjects aged 20-60 years. The validated results were compared with those from a double stethoscope check. We observed mean absolute errors of 4.77 and 4.24 mm Hg in estimating the SBP and DBP, respectively.