Melt differential centrifugal electrospinning (MDCE) method is proposed by integrating the advantages of centrifugal spinning and melt differential electrospinning, including high efficiency, solvent-free, multiple jets formation from nozzle-less spinning system, and small diameter. A mathematical model of jet diameter in MDCE is established. An orthogonal experiment is carried out to explore the effects of main processing parameters on the average diameter and the diameter standard deviation of the prepared fibers. Ultimately, polypropylene (PP) nanofibers with an average diameter of 790 nm are successfully prepared in a higher flow rate of 124.26 g h −1 than that of other methods. The X-ray diffraction and differential scanning calorimeter indicate that the introduction of high-voltage electrostatic field in centrifugal spinning contribute to the crystal orientation of the PP molecular chain. Therefore, tensile mechanical strength is enhanced as the increase of the loading voltage. MDCE may provide an efficient and eco-friendly method for nanofiber manufacturing in the future.

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Polyphenylene sulfide (PPS) nanofibers have broad application prospects in high temperature dust removal, high temperature oil-water separation, radiation protection, and other fields. PPS nanofibers were prepared by melt differential electrospinning without any other additives, which ensures the excellent properties of PPS fibers. The effects of spinning parameters (spinning voltage, spinning distance, spinning temperature) on the morphology of PPS fibers were systematically studied, and the average diameter of PPS fibers with 1.28 μm was obtained under the optimum conditions (spinning distance of 6 mm, temperature of 310 C and spinning voltage of 35 kV). The effect of spinning voltage on the crystallinity and thermal stability of the fiber was analyzed. Finally, the filtration efficiencies of the commercial dust-proof filter bags and the obtained PPS fibers with the same weight were compared. It was demonstrated that filtration efficiency of the obtained PPS fibers with 186 g/cm 2 reached up to 99.95%. This study aims to provide a new idea for green industrial manufacturing and application of electrospinning PPS nanofibers.

This paper considers vital signs (VS) such as respiration movement detection of human subjects using an impulse ultra-wideband (UWB) through-wall radar with an improved sensing algorithm for random-noise de-noising and clutter elimination. One filter is used to improve the signal-to-noise ratio (SNR) of these VS signals. Using the wavelet packet decomposition, the standard deviation based spectral kurtosis is employed to analyze the signal characteristics to provide the distance estimate between the radar and human subject. The data size is reduced based on a defined region of interest (ROI), and this improves the system efficiency. The respiration frequency is estimated using a multiple time window selection algorithm. Experimental results are presented which illustrate the efficacy and reliability of this method. The proposed method is shown to provide better VS estimation than existing techniques in the literature.

This paper presents a new time of arrival (TOA) estimation technique using an improved energy detection (ED) receiver based on the empirical mode decomposition (EMD) in an impulse radio (IR) 60 GHz millimeter wave (MMW) system. A threshold is employed via analyzing the characteristics of the received energy values with an extreme learning machine (ELM). The effect of the channel and integration period on the TOA estimation is evaluated. Several well-known ED-based TOA algorithms are used to compare with the proposed technique. It is shown that this ELM-based technique has lower TOA estimation error compared to other approaches and provides robust performance with the IEEE 802.15.3c channel models.