A Fundamental Wave Amplitude Prediction Algorithm Based on Fuzzy Neural Network for Harmonic Elimination of Electric Arc Furnace Current

Electric arc furnace (EAF) causes the harmonics to impact on the supply network greatly and harmonic elimination is a very important research work for the power quality associated with EAF. In the paper, a fundamental wave amplitude prediction algorithm based on fuzzy neural network for harmonic elimination of EAF current is proposed. The proposed algorithm uses the learning ability of the neural network to refine Takagi-Sugeno type fuzzy rules and the inputs are the average of the current measured value in different time intervals. To verify the effectiveness of the proposed algorithm, some experiments are performed to compare the proposed algorithm with the back-propagation neural networks, and the field data collected at an EAF are used in the experiments. Moreover, the measured amplitudes of fundamental waves of field data are obtained by the sliding-window-based discrete Fourier transform on the field data. The experiments results show that the proposed algorithm has higher precision. The real curves also verify that the amplitude of fundamental wave current could be predicted accurately and the harmonic elimination of EAF would be realized based on the proposed algorithm

Single-cell sequencing reveals CD133+CD44--originating evolution and novel stemness related variants in human colorectal cancer

BACKGROUND: Tumor heterogeneity of human colorectal cancer (CRC)-initiating cells (CRCICs) in cancer tissues often represents aggressive features of cancer progression. For high-resolution examination of CRCICs, we performed single-cell whole-exome sequencing (scWES) and bulk cell targeted exome sequencing (TES) of CRCICs to investigate stemness-specific somatic alterations or clonal evolution. METHODS: Single cells of three subpopulations of CRCICs (CD133+CD44+, CD133-CD44+, and CD133+CD44- cells), CRC cells (CRCCs), and control cells from one CRC tissue were sorted for scWES. Then, we set up a mutation panel from scWES data and TES was used to validate mutation distribution and clonal evolution in additional 96 samples (20 patients) those were also sorted into the same three groups of CRCICs and CRCCs. The knock-down experiments were used to analyze stemness-related mutant genes. Neoantigens of these mutant genes and their MHC binding affinity were also analyzed. FINDINGS: Clonal evolution analysis of scWES and TES showed that the CD133+CD44- CRCICs were the likely origin of CRC before evolving into other groups of CRCICs/CRCCs. We revealed that AHNAK2, PLIN4, HLA-B, ALK, CCDC92 and ALMS1 genes were specifically mutated in CRCICs followed by the validation of their functions. Furthermore, four predicted neoantigens of AHNAK2 were identified and validated, which might have applications in immunotherapy for CRC patients. INTERPRETATION: All the integrative analyses above revealed clonal evolution of CRC and new markers for CRCICs and demonstrate the important roles of CRCICs in tumorigenesis and progression of CRCs. FUNDING: A full list of funding bodies that contributed to this study can be found in the Acknowledgements section

GroundNLQ @ Ego4D Natural Language Queries Challenge 2023

In this report, we present our champion solution for Ego4D Natural Language Queries (NLQ) Challenge in CVPR 2023. Essentially, to accurately ground in a video, an effective egocentric feature extractor and a powerful grounding model are required. Motivated by this, we leverage a two-stage pre-training strategy to train egocentric feature extractors and the grounding model on video narrations, and further fine-tune the model on annotated data. In addition, we introduce a novel grounding model GroundNLQ, which employs a multi-modal multi-scale grounding module for effective video and text fusion and various temporal intervals, especially for long videos. On the blind test set, GroundNLQ achieves 25.67 and 18.18 for R1@IoU=0.3 and R1@IoU=0.5, respectively, and surpasses all other teams by a noticeable margin. Our code will be released at\url{https://github.com/houzhijian/GroundNLQ}.Comment: 5 pages, 2 figures, 4 tables, the champion solution for Ego4D Natural Language Queries Challenge in CVPR 202

Researching of Image Compression Based on Quantum BP Network

The encoding time of traditional fractal image coding method is too long.Aiming at this problem, a quantum BP network algorithm is proposed in the paper. By using a neuronal model with quantum input and output, combined with the theory of BP in image compression and the complex BP algorithm, a model for image impression with 3-layer quantum BP is built, which implements image compression and image reconstruction. The simulation results show that QBP can obtain the reconstructed images with better quantity compared with BP in spite of the less learning iterations. DOI: http://dx.doi.org/10.11591/telkomnika.v11i11.355

Optimization Configuration of Grid-Connected Inverters to Suppress Harmonic Amplification in a Microgrid

This paper provides insight into the optimal configuration scheme of the grid-connected inverters based on harmonic amplification suppression. The connection of the inverters changes the natural resonance frequencies of the grid. Hence, a reasonable configuration of grid-connected inverters can optimize the impedance distribution and shift the natural resonance frequencies to frequency bands farther away from the harmonic sources. We proposed a scheme of site selection and determination of the number of inverters to suppress harmonic amplification. The resonance frequencies and modal frequency sensitivities (MFSs) were obtained by the resonance modal analysis (RMA). Moreover, the concepts of security region and insecurity region of resonance frequency were illustrated. The grid-connected sites can be obtained by calculating the participation factors (PFs) of the resonance frequencies in the insecurity region. Furthermore, the optimal number was determined by building the Norton equivalent circuit of the inverter and evaluating the output impedance at each frequency. Finally, simulations in Matlab/Simulink based on a modified IEEE-9 bus microgrid were utilized to verify the effectiveness of the proposed scheme

Modeling and Enhanced Error-Free Current Control Strategy for Inverter with Virtual Resistor Damping

In microgrid, the grid-connected inverter current with the LCL (inductor-capacitor-inductor) output filter is amplified at certain frequencies. Using virtual resistor damping method can help suppress the amplification. By choosing an appropriate virtual resistor value, the model of the inverter current control loop is simplified as a 2nd-order lowpass filter. Based on such simplified model, this paper proposes a design method of reference current compensation controller, which does not require decomposition of harmonic components. With the reference compensation, the inverter output current control precision is improved obviously. The simulation and experimental results verify the accuracy of the inverter simplified model and effectiveness of the reference compensation design method

Comprehensive Analysis of Alternative Splicing in <i>Digitalis purpurea</i> by Strand-Specific RNA-Seq

<div><p><i>Digitalis purpurea</i> (<i>D. purpurea</i>) is one of the most important medicinal plants and is well known in the treatment of heart failure because of the cardiac glycosides that are its main active compounds. However, in the absence of strand specific sequencing information, the post-transcriptional mechanism of gene regulation in <i>D. purpurea</i> thus far remains unknown. In this study, a strand-specific RNA-Seq library was constructed and sequenced using Illumina HiSeq platforms to characterize the transcriptome of <i>D. purpurea</i> with a focus on alternative splicing (AS) events and the effect of AS on protein domains. <i>De novo</i> RNA-Seq assembly resulted in 48,475 genes. Based on the assembled transcripts, we reported a list of 3,265 AS genes, including 5,408 AS events in <i>D. purpurea</i>. Interestingly, both glycosyltransferases and monooxygenase, which were involved in the biosynthesis of cardiac glycosides, are regulated by AS. A total of 2,422 AS events occurred in coding regions, and 959 AS events were located in the regions of 882 unique protein domains, which could affect protein function. This <i>D. purpurea</i> transcriptome study substantially increased the expressed sequence resource and presented a better understanding of post-transcriptional regulation to further facilitate the medicinal applications of <i>D. purpurea</i> for human health.</p></div

Stability analysis of digitally controlled dual active bridge converters

Abstract The dual active bridge (DAB) converters are widely used in the energy storage equipment and the distributed power systems. However, the existence of switching nonlinearity and control delay can cause serious stability problem to the DAB converters. Thus, this paper, studies the stability of a digitally controlled DAB converter with an output voltage closed loop controller. Firstly, to accurately study the stability in a DAB converter, a discrete-time model established in a whole switching period is obtained. The model considers the output capacitor ESR, the digital control delay, and sample-and-hold process. By using this model, the stabilities of the DAB converter versus the proportional controller parameter and the output capacitor ESR are analyzed and the critical values are predicted accurately. Moreover, the stability boundary of the proportional controller parameter and the output capacitor ESR is also obtained. The result shows that the value of the output capacitor ESR can have a great effect on the stability region of the proportional controller parameter. Finally, the theoretical analyses are verified by the simulation and experimental results