In the present study, tin nanoparticles were green-synthesized using the aqueous extract of Foeniculum vulgare leaf aqueous extract. The synthesized SnNPs were characterized by analytical techniques including EDX, FE-SEM, XRD, UV-Vis., and FT-IR. The anti-human gastric cancer activity of SnNPs was evaluated using MTT assay. The nanoparticles were formed in a spherical shape in the range size of 26.45 to 38.53 nm. In the antioxidant test, the IC50 of F. vulgare, SnNPs@FV, and BHT against DPPH free radicals were 384, 119, and 71 µg/mL, respectively. In the cellular and molecular part of the recent study, the treated cells with SnNPs@FV were assessed by MTT assay for 48h about the cytotoxicity and anti-human lung cancer properties on normal (HUVEC) and lung cancer cell lines i.e., NCI-H2126, NCI-H1299, and NCI-H1437. The IC50 of SnNPs@FV were 108, 168, and 122 µg/mL against NCI-H2126, NCI-H1299, and NCI-H1437 cell lines, respectively. The viability of malignant lung cell line reduced dose-dependently in the presence of SnNPs@FV.

Multi-terminal high-voltage direct current technology based on voltage-source converter stations (VSC-MTDC) is expected to be one of the most important contributors to the future of electric power systems. In fact, among other features, it has already been shown how this technology can contribute to improve transient stability in power systems by the use of supplementary controllers. Along this line, this paper will investigate in detail how these supplementary controllers affect electromechanical oscillations, by means of small-signal stability analysis. The paper analyses two control strategies based on the modulation of active-power injections (P-WAF) and reactive-power injections (Q-WAF) in the VSC stations which were presened in previous work. Both control strategies use global signals of the frequencies of the VSC-MTDC system and they presented significant improvements on transient stability. The paper will provide guidelines for the design of these type of controllers to improve both, large- and small-disturbance angle stability. Small-signal stability analysis (in Matlab) has been compared with non-linear time domain simulation (in PSS/E) to confirm the results using CIGRE Nordic32A benchmark test system with a VSC-MTDC system. The paper analyses the impact of the controller gains and communication latency on electromechanical-oscillation damping. The main conclusion of the paper is that transient-stability-tailored supplementary controllers in VSC-MTDC systems can be tuned to damp inter-area oscillations too, maintaining their effectiveness.

With the development of smart distribution network and the proposal of dual carbon target, the importance of demand side management in improving the flexible operation of power system is becoming more and more prominent. In order to solve the problems of excessive load peak valley difference, insufficient utilization of demand side resources, and unreasonable pricing of aggregators, this paper propose an economic optimization scheme for aggregators based on electric vehicle three-stage dispatching. First, the loss aversion analysis is conducted on the willingness of electric vehicle users to participate in dispatching. The contract signing methods between aggregators and electric vehicles are divided into three categories: complete dispatching, rolling reward and punishment mechanism dispatching, and free dispatching. Next, the response model of electric vehicle users based on the improved cloud model is obtained. Then, the aggregators conduct three-phase optimal dispatching for electric vehicles according to the bid winning peak shaving capacity. Phase 1 according to the time of regional differences, the dispatching of reward power set rewards and punishment mechanism, phase 2 to determine the full freedom dispatching of electric vehicles, three kinds of dispatching and dynamic load capacity of electricity, phase 3 according to the phase 1 and 2, the amount of information and user loss aversion, the user response model of final rolling rewards and punishment mechanism, get the aggregators final pricing schemes, Finally, a numerical example is given to verify the feasibility of the proposed method.

In this paper, the impact of residential photovoltaic (PV) battery systems in a real test system with the goal of system peak load shaving is investigated. In order to encourage residential investors, a Levelized feed-in tariff (LFiT) scheme is introduced. Accordingly, two proposed cases and relevant suggestions are presented to reach a better performance. The profitability of the project is apprised via several economic criteria such as net present value (NPV), payback period years (PBY), internal rate of return (IRR), benefit to cost ratio (BCR), net cash flow (NCF), and Levelized cost of energy (LCOE). Moreover, different levels of peak shaving subject to customers’ participation and the size of the PV-battery system are also obtained. An actual test system regarding one-year recorded data is employed to elevate the precise of results. Furthermore, results are economically compared with the current situation in the test system to assess the effectiveness of the suggested system. Obtained results determine the best size of PV and battery to attain the preferable profitability. Meanwhile, the LFiT with respect to the economic criteria is specified as well. Finally, a sensitivity analysis on systems’ parameters is performed to identify the impact of these parameters on economic indices.

In this letter, the issue of mitigating strong co-channel interference (CCI) in communication systems is addressed. Unlike conventional model-based methods, a novel data-driven scheme is proposed. A recurrent neural network (RNN) is trained to directly demodulate the desired signal under strong CCI. Instead of inputting the original received signal, in-phase and quadrature interference-robust features (IRF) are extracted through preprocess. The RNN is then trained offline to implement sequence labelling, with the IRF sequences and known code sequences of the desired signal as inputs and ground-truth labels. Meanwhile, a guard zone is introduced when loading the IRF sequences to enable better contextual information exploitation by the RNN demodulator. Online tests validated the low bit error rate (BER) of the RNN demodulator, under strong CCI. Moreover, the proposed scheme outperformed existing model-based and data-driven interference mitigation schemes in terms of the BER, especially in low signal-to-interference ratio region. Inspiringly, the proposed data-driven scheme generalized well to varied unseen test conditions.

The effect of niobium ion with high valence doping on high voltage LiNi0.5Mn1.5O4 materials was investigated. LiNi0.5Mn1.5-xNbxO4 was prepared by doping high-valent niobium ion into LiNi0.5Mn1.5O4 material using the organic assisted combustion method. The experimental samples were characterized by scanning electron microscopy, transmission electron microscopy, X-ray diffraction, X-ray photoelectron spectroscopy and electrochemical impedance analysis. The experimental results show that the doping with high valence niobium ion change the orientation of the crystal plane growth of spinel particles, and the morphology of these particles change from the octahedral shape before doping to the spherical shape after doping. With the increase of doping amount, the crystal structure changes gradually, resulting in the Li0.96Nb1.01O3 impurity phase. The doping of high valence niobium ion increases the content of Mn3+ in the material, resulting in the appearance of a 4 V discharge platform, and the formation of a 4.7 V and 4 V discharge platform. The doping of Nb can improve the cycling stability of LiNi0.5Mn1.5O4 material, but the specific capacity of the material is reduced.

Beamforming technique can effectively improve the spectrum utilization of multi-antenna systems, while the dirty-paper coding (DPC) technique can reduce inter-user interference. In this letter, we aim to maximize the weighted sum-rate under power constraint in a multiple-input-single-output (MISO) system with the DPC. However, the existing methods of beamforming optimization mainly rely on customized iterative algorithms, which have high computational complexity. To address this issue, by utilizing the deep learning technique and the uplink-downlink duality, and carefully exploring the optimal solution structure, we devise a beamforming neural network (BFNNet), which includes a deep neural network module and a signal processing module. Besides, we use the modulus of the channel coefficients as the input of deep neural network, which reduces the input size. Simulation results show that a well-trained BFNNet can achieve near-optimal solutions, while significantly reducing computational complexity

A document by Yi Zhang. Click on the document to view its contents.

The iron core in the circuit breaker of oil dashpot is mainly affected by the electromagnetic force, spring force and oil damping force, which can play the function of anti-time protection when overload current is excited. At low temperature, the viscosity of the methyl silicone oil damping fluid will change, and the parameters of spring and iron core will also change with temperature. The change of this parameters will lead to the change of the resultant force on the iron core, which will affect the operation time. To analyze this problem, a correlation model is established. Through the measurement of parameters at low temperature, numerical calculation, electromagnetic analysis, simulation analysis and compared with the experimental results. The study found that the viscosity of the damping fluid increases, the iron core is deformed, and the spring stiffness increases at low temperature. The influence of a single factor on the operation characteristics of the tripper is not enough to reflect its overall characteristics, and the comprehensive effect of each factor needs to be considered. After comprehensively considering all factors, the results are closer to the experimental results. The results provide a theoretical basis for the optimization design of the circuit breaker.

The improvement of the performance of a distributed Bragg reflector laser bar emitting near 905 nm through the use of multiple epitaxially stacked active regions and tunnel junctions is reported. The bar consisting of 48 emitters (each having an aperture of 50 μm) emits an optical power of 2.2 kW in 8 ns long pulses at an injection current of 1.1 kA. This corresponds to an almost threefold increase of the pulse power compared to a bar with lasers having only a single active region. Due to the integrated surface Bragg grating, the bar exhibits a narrow spectral bandwidth of about 0.3 nm and a thermal tuning of only 68 pm/K.

In this letter, a novel sext-band bandpass filter (BPF) using two split-type multiple-mode resonators is proposed. The filter is composed of two sets of resonators which are respectively designed to realize Filter 1 with two passbands and Filter 2 with quad passbands. Then the two BPFs are combined by parallel coupling feed lines for sext-band responses, and each of the six centre frequencies in the proposed sext-band BPF is able to be controlled due to the design freedom. To validate the design and analysis, a prototype filter has been fabricated with six passbands centered at 1.88/2.59/3.48/5.26/5.82/6.75 GHz. The measured result of the fabricated filter agrees well with the simulation, which shows that the proposed structure is a good candidate for sext-band BPF designs and validates the proposed design flow well.

The health monitoring for disease diagnosis and prognosis in a desired smart medical structure is realized by interpreting the health data. The advances in sensor technologies and biomedical data acquisition tools have led to the new era of big data, where different sensors collect massive medical data every day. This special issue explores the latest development in emerging technologies of biomedical engineering, including big medical data, artificial intelligence, cloud/fog computing, federated learning, ubiquitous computing and communication, internet of things, wireless technologies, and, security and privacy. The biological wearable sensors can enhance the decision-making and early disease diagnosis processes by intelligently investigating and collecting large amounts of biomedical data (i.e., big health data). Hence, there is a need for scalable advanced learning, and intelligent algorithms that lead to reliable and interoperable solutions to make effective decisions in emergency medicine technologies. The optimization algorithms can be used in order to acquire the sensor data from multiple sources for fast and accurate health monitoring.

In the real environment, the unstable radar measurement noise can degrade the tracking performance of the maneuvering target. In this Letter, the iterative formulation of the noise is simplified, and the noise-adaptive matrix is introduced to calculate the fading factor of the strong tracking algorithm, so that the effect of measurement noise on the fading factor can be corrected in real time. The superior performance of the proposed method is verified by comparison with three existing improved methods on a typical example.

The existing prefabricated wireline construction technology is difficult to accurately measure the real-time length of the deployed wires, resulting in too large construction errors and cannot be popularized and applied. To this end, a length measuring device that can accurately measure the length of the wire during the construction of the prefabricated wire is developed. In terms of the hardware of the length measuring equipment, based on the construction characteristics of the prefabricated wiring and the characteristics of the wire, the photoelectric encoder and the STC8G series single chip microcomputer are used to complete the collection and processing of the wire length data, and the mature and stable LoRa technology is used to complete the wireless transmission of the data. In terms of software program of length measurement equipment, the measurement of wire length data, transmission and interaction of control command signals are realized by optimizing length measurement scheme, interface development of terminal equipment and information interaction program design. Finally, according to the actual working conditions of the prefabricated wiring construction, the mechanical structure of the length measuring equipment is designed, and the assembly is completed. The developed length measuring equipment has been successfully applied to practical projects. According to the wire length measuring equipment, the deviation between the observation sag and the design sag after the wire length is measured by the wire length measuring equipment is 2.0%, which meets the design requirement of ±2.5%.

An ultra-low profile and high-performance UHF RFID reader antenna is proposed in this letter, which can be switched between far-field (FF) and near-field (NF) operative mode. This antenna is composed of four dipoles and a reconfigurable feed network. The four dipoles form a square, and the feed network is located in the center. The feed network is a four-way power divider, and the phase of the output signal can be controlled by switching diodes. As a balanced structure, double-sided parallel-strip lines (DSPSLs) are used to feed four dipoles. Compared to the balun structure, the application of DSPSLs can reduce the area of the feed network, thereby reducing the influence of the feed network on the central magnetic field. Experimental results show that the proposed antenna can provide a NF reading area of 180×180 mm2, and the identification rate can reach 100% within 30-60 mm height. The FF gain of the antenna is 4.7 dBic, and the overlapping range of 3 dB AR bandwidth and -10 dB impedance bandwidth is 800-960 MHz. The good FF and NF performance of this antenna is conducive to its application in RFID systems.

In this study, the Zn nanoparticles was synthesized using the peel extract of Citrus aurantium. The nanoparticles was characterized by different chemical technique including UV-Vis. and FT-IR spectroscopy, and SEM technique. The results revealed a spherical shape in the average ‎size of 41.17 nm was identified for the green-synthesized nanoparticles. In the antioxidant test, the IC50 of nanoparticles and BHT against DPPH free radicals were 115 and 96 µg/mL, respectively. In the cellular and molecular part of the recent study, the treated cells with nanoparticles were assessed by MTT assay for 48h about the cytotoxicity and anti-human gastric cancer properties on normal (HUVEC) and gastric cancer cell lines i.e. NCI-N87 and MKN45. The IC50 of nanoparticles were 278 and 256 µg/mL against NCI-N87 and MKN45 cell lines, respectively. The viability of malignant gastric cell line reduced dose-dependently in the presence of Zn nanoparticles. It seems that the anti-human gastric cancer effect of recent nanoparticles is due to their antioxidant effects. After evaluating the effectiveness of this formulation in clinical trial researches, it can be a good alternative to chemotherapy drugs.

A novel frequency-to-voltage converter (FVC) based phase-locked loop (PLL) is proposed to overcome the inability of an FVC-based frequency-locked loop (FLL) to lock phase. The proposed dual-loop PLL adds variable phase-locking capability, such that the phase locking angle can vary from 0o – 360o. The additional variable phase-locking can be applied in data communication in the form of phase modulation. The design is targeted for a 0.5-µm CMOS process. The proposed design generates a 480MHz clock from a reference clock of 15MHz. In simulation, the proposed PLL locks within 3.56 µs while consuming 1.61 mW of power.

Automatic dependent surveillance-broadcast (ADS-B) has been widely used due to its low cost and high precision. The deep learning methods for ADS-B signal classification have achieved a high performance. However, recent studies have shown that deep learning networks are very sensitive and vulnerable to small noise. We propose an ADS-B signal poisoning method based on U-Net. This method can generate poisoned signals. We assign one of ADS-B signal classification networks as the attacked network and another one as the protected network. When poisoned signals are fed into these two well-performed classification networks, the poisoned signal will recognized incorrectly by the attacked network while classified correctly by the protected network. We further propose an Attack-Protect-Similar loss to achieve “triple-win” in leading attacked network poor performance, protected network well performance and the poisoned signals similar to unpoisoned signals. Experimental results show attacked network classifies poisoned signals with a 1.55% classification accuracy, while the protected network classifies rate is still maintained at 99.38%.