Efficient Aperture Fill Time Correction for Wideband Sparse Array Using Improved Variable Fractional Delay Filters.

To solve the problem of aperture fill time (AFT) for wideband sparse arrays, variable fractional delay (VFD) FIR filters are applied to eliminate linear coupling between spatial and time domains. However, the large dimensions of the filter coefficient matrix result in high system complexity. To alleviate the computational burden of solving VFD filter coefficients, a novel multi-regultion minimax (MRMM) model utilizing the sparse representation technique has been presented. The error function is constrained by the introduction of L2-norm and L1-norm regularizations within the minimax criterion. The L2-norm effectively resolves the problems of overfitting and non-unique solutions that arise in the sparse optimization of traditional minimax (MM) models. Meanwhile, the use of multiple L1-norms enables the optimal design of the smallest sub-filter number and order of the VFD filter. To solve the established nonconvex model, an improved sequential-alternating direction method of multipliers (S-ADMM) algorithm for filter coefficients is proposed, which utilizes sequential alternation to iteratively update multiple soft-thresholding problems. The experimental results show that the optimized VFD filter reduces system complexity significantly and corrects AFT effectively in a wideband sparse array.

Efficient Multi-Sound Source Localization Algorithm for Transformer Faults Based on Polyphase Filters.

Power transformers play a critical role in power systems, and the early detection of their faults and defects, accounting for over 30%, can be achieved through abnormal sound analysis. Sound source localization based on microphone arrays has proven effective in focusing on the troubleshooting scope, preventing potential severe hazards caused by delays in fault removal, and significantly reducing operational and maintenance difficulties and costs. However, existing microphone array-based sound source localization algorithms face challenges in maintaining both accuracy and simplicity and especially suffer from a sharp decrease in performance when dealing with multiple sound sources. This paper presents a multi-sound source localization algorithm for transformer faults based on polyphase filters, integrating the sum-difference monopulse angle measurement technique into the microphone array. Firstly, the signals received from the transformers are divided into multiple subbands using polyphase filters, allowing for multi-source separation and reducing the sampling rate of each subband. Next, the time-domain signals in subbands subject to noise suppression are processed into sum and difference beams. The resulting beam outputs are transformed into frequency-domain signals using the Fast Fourier Transform (FFT), effectively enhancing the signal-to-noise ratio (SNR) for separate sound sources. Finally, each subband undergoes sum-difference monopulse angle measurement in the frequency domain to achieve the high-precision localization of specific faults. The proposed algorithm has been demonstrated to be effective in achieving higher localization accuracy and reducing computational complexity in the presence of actual amplitude-phase errors in microphone arrays. These advantages can facilitate its practical applications. By enabling early targeting of fault sources when abnormalities occur, this algorithm provides valuable assistance to operation and maintenance personnel, thereby enhancing the maintenance efficiency of transformers.

Enhanced carbon dioxide fixation of Chlorella vulgaris in microalgae reactor loaded with nanofiber membrane carried iron oxide nanoparticles.

To improve the CO2 dissolution and carbon fixation in the process of microalgae capturing CO2 from flue gas, a nanofiber membrane containing iron oxide nanoparticles (NPsFe2O3) for CO2 adsorption was prepared, and coupled with microalgae utilization to achieve carbon removal. The performance test results showed that the largest specific surface area and pore size were 8.148 m2 g-1 and 27.505 Å, respectively, when the nanofiber membrane had 4% NPsFe2O3. Through CO2 adsorption experiments, it was found that the nanofiber membrane could prolong the CO2 residence time and increase CO2 dissolution. Then, the nanofiber membrane was used as a CO2 adsorbent and semifixed culture carrier in the Chlorella vulgaris culture process. The results showed that compared with the group without nanofiber membrane (0 layer), the biomass productivity, CO2 fixation efficiency and carbon fixation efficiency of Chlorella vulgaris with 2 layers of membranes increased by 1.4 times.

Towards stimulated Raman scattering spectro-microscopy across the entire Raman active region using a multiple-plate continuum.

Stimulated Raman scattering (SRS) has attracted increasing attention in bio-imaging because of the ability toward background-free molecular-specific acquisitions without fluorescence labeling. Nevertheless, the corresponding sensitivity and specificity remain far behind those of fluorescence techniques. Here, we demonstrate SRS spectro-microscopy driven by a multiple-plate continuum (MPC), whose octave-spanning bandwidth (600-1300 nm) and high spectral energy density (∼1 nJ/cm-1) enable spectroscopic interrogation across the entire Raman active region (0-4000 cm-1), SRS imaging of a Drosophila brain, and electronic pre-resonance (EPR) detection of a fluorescent dye. We envision that utilizing MPC light source will substantially enhance the sensitivity and specificity of SRS by implementing EPR mode and spectral multiplexing via accessing three or more coherent wavelengths.

Enhanced photoautotrophic growth of Chlorella vulgaris in starch wastewater through photo-regulation strategy.

Microalgae biomass production with starch wastewater (SW) is a promising approach to realize waste recovery and cost reduction due to the inherent copious nutrients and nontoxic compounds in SW. However, the application of this technique is significantly hindered by low biomass production on account of the poor photosynthetic efficiency of microalgae. In this regard, we proposed a photo-regulation strategy characterized by the adjusting of numbers of light/dark (L/D) cycles, and compositions of light wavelength, which was proved to be an effective method for stimulating intracellular photo electron transfer and enhancing photosynthetic efficiency, to boost microalgae biomass accumulation. Additionally, responses of the microalgae photo-biochemical conversion, and the wastewater treatment performance at various number of L/D cycles and light wavelengths were discussed. The experimental results indicated that the biomass production increased when the L/D period was increased from 2 h:2 h-12 h:12 h. When the L/D period was 2 h:2 h, the biomass production reached a maximum value of 1.28 g L-1, which was 19.6% higher than that of the control group when the L/D period was 12 h:12 h. Furthermore, with respect to microalgae growth under monochromatic light, the maximum biomass concentration (1.25 g L-1) and lipid content (32.2%) of Chlorella were achieved under blue light; whereas, the minimum values were attained under red light (1.05 g L-1 and 19.3%, respectively). When the red light and blue light were mixed and supplied, the microalgae biomass productivity was higher than that under white light, and the highest lipid productivity was 109.0 mg-1 L-1 d under a blue: red ratio of 2:1. Moreover, gas chromatography analysis demonstrated that the methyl in the range of C16-C18 in the system was higher than 70%. Fatty acid methyl esters (FAMEs) containing palmitic acid (C16:0) and oleic acid (C18:1) are beneficial for production of biodiesel, and the quality of fatty acid methyl ester used in biodiesel production can be improved using microalgae cultured under the mixed wavelengths of blue and red. Finally, Chlorella was cultured in PBR and reached the peak concentration of 2.45 g L-1 by semi-continuous process with the HRT regulation.

Synergistic Effects of Micro-electrolysis-Photocatalysis on Water Treatment and Fish Performance in Saline Recirculating Aquaculture System.

A new physico-chemical process for TAN (total ammonia nitrogen) removal and disinfection is introduced in saline recirculating aquaculture system (RAS), in which the biofilter is replaced with an integrated electrolysis cell and an activated carbon filter. The electrolysis cell which is based on micro current electrolysis combined with UV-light was self-designed. After the fundamental research, a small pilot scale RAS was operated for 30 days to verify the technical feasibility. The system was stocked by 42 GIFT tilapia (Oreochromis niloticus) fish with the rearing density of 13 kg/m3. During the experiments, the TAN concentration remained below 1.0 mg/L. The nitrite concentration was lower than 0.2 mg/L and the nitrate concentration had increased continuously to 12.79 mg/L at the end. Furthermore, the concentration of residual chlorine in culture ponds remained below 0.3 mg/L, ORP maintained slight fluctuations in the range of 190~240 mV, and pH of the water showed the downtrend. Tilapia weight increased constantly to 339.3 ± 10 g. For disinfection, the active chlorine generated by electrochemical treatment caused Escherichia coli inactivation. Enzyme activity assay indicated that the activity of glutamate dehydrogenase, carbonic anhydrase and glutamic pyruvic transaminase increased within the normal range. The preliminary feasibility was verified by using this physico-chemical technology in the RAS.

An Efficient Adaptive Angle-Doppler Compensation Approach for Non-Sidelooking Airborne Radar STAP.

In this study, the effects of non-sidelooking airborne radar clutter dispersion on space-time adaptive processing (STAP) is considered, and an efficient adaptive angle-Doppler compensation (EAADC) approach is proposed to improve the clutter suppression performance. In order to reduce the computational complexity, the reduced-dimension sparse reconstruction (RDSR) technique is introduced into the angle-Doppler spectrum estimation to extract the required parameters for compensating the clutter spectral center misalignment. Simulation results to demonstrate the effectiveness of the proposed algorithm are presented.

An efficient moving target detection algorithm based on sparsity-aware spectrum estimation.

In this paper, an efficient direct data domain space-time adaptive processing (STAP) algorithm for moving targets detection is proposed, which is achieved based on the distinct spectrum features of clutter and target signals in the angle-Doppler domain. To reduce the computational complexity, the high-resolution angle-Doppler spectrum is obtained by finding the sparsest coefficients in the angle domain using the reduced-dimension data within each Doppler bin. Moreover, we will then present a knowledge-aided block-size detection algorithm that can discriminate between the moving targets and the clutter based on the extracted spectrum features. The feasibility and effectiveness of the proposed method are validated through both numerical simulations and raw data processing results.