A Novel Crosstalk Elimination Method for Sonar Ranging System in Rescue Robot

AbstractUltrasonic crosstalk can cause false distance measurements and reduce the work efficiency of sonar ranging system. To enhance the performance of sonar ranging system in rescue robot, quadrature phase shift keying (QPSK) excitation sequences modulated using chaotic codes are proposed to fire sonar sensors. In order to obtain the best echo correlation characteristics, a genetic algorithm (GA) is used to optimize the initial values of the chaotic codes. Real experiments have been implemented using a sonar ranging system consisting of eight-channel SensComp 600 series electrostatic sensors excited with 2ms QPSK sequences. Experimental results show that the optimized QPSK excitation sequences can make eight channels sonar ranging system work together without crosstalk

(1)H, (15)N and (13)C backbone resonance assignments of the Kelch domain of mouse Keap1.

Kelch-like ECH-associated Protein 1 (Keap1) is a multi-domain protein that functions as an inhibitor of the transcription factor nuclear factor E2-related factor 2 (Nrf2) in the cellular response to oxidative stress. Under normal conditions, Keap1 binds to Nrf2 via its C-terminal Kelch domain and the interaction ultimately leads to the ubiquitin-dependent degradation of Nrf2. It has been proposed that designing molecules to selectively disrupt the Keap1-Nrf2 interaction can be a potential therapeutic approach for enhancing the expression of cytoprotective genes. Here, we reported the (1)H, (13)C, and (15)N backbone chemical shift assignments of the Kelch domain of mouse Keap1. Further, unlabeled Nrf2 peptide containing the Kelch-binding motif was added to the (15)N-labeled Kelch sample. (1)H-(15)N HSQC spectra of the protein in the absence and presence of an equimolar concentration of the Nrf2 peptide were presented. A significant number of resonance signals were shifted upon addition of the peptide, confirming the protein-peptide interaction. The results here will not just facilitate the further studies of the binding between Keap1 and Nrf2, it will also be valuable for probing interactions between the Kelch domain and small molecules, as well as a growing list of protein targets that have been identified recently

Incremental capacity curve health-indicator extraction based on gaussian filter and improved relevance vector machine for lithium–ion battery remaining useful life estimation.

Accurate prediction of the remaining useful life (RUL) of lithium–ion batteries is the focus of lithium–ion battery health management. To achieve high–precision RUL estimation of lithium–ion batteries, a novel RUL prediction model is proposed by combining the extraction of health indicators based on incremental capacity curve (IC) and the method of improved adaptive relevance vector machine (RVM). First, the IC curve is extracted based on the charging current and voltage data. To attenuate the noise effects on the IC curve, Gaussian filtering is used and the optimal filtering window is determined to remove the noise interference. Based on this, the peak characteristics of the IC curve are analyzed and four groups of health indicators are extracted, and the strong correlation between health indicators and capacity degradation is determined using Pearson correlation analysis. Then, to optimize the traditional fixed kernel parameter RVM model, an RVM regression model whose kernel parameters are optimized by the Bayesian algorithm is established. Finally, four sets of datasets under CS2 battery in the public dataset of the University of Maryland are carried out for experimental validation. The validation results show that the improved RVM model has better short–term prediction performance and long–term prediction stability, the RUL prediction error is less than 20 cycles, and the mean absolute error is less than 0.02. The performance of the improved RVM model is better than that of the traditional RVM model

M3PT: A Multi-Modal Model for POI Tagging

POI tagging aims to annotate a point of interest (POI) with some informative tags, which facilitates many services related to POIs, including search, recommendation, and so on. Most of the existing solutions neglect the significance of POI images and seldom fuse the textual and visual features of POIs, resulting in suboptimal tagging performance. In this paper, we propose a novel Multi-Modal Model for POI Tagging, namely M3PT, which achieves enhanced POI tagging through fusing the target POI's textual and visual features, and the precise matching between the multi-modal representations. Specifically, we first devise a domain-adaptive image encoder (DIE) to obtain the image embeddings aligned to their gold tags' semantics. Then, in M3PT's text-image fusion module (TIF), the textual and visual representations are fully fused into the POIs' content embeddings for the subsequent matching. In addition, we adopt a contrastive learning strategy to further bridge the gap between the representations of different modalities. To evaluate the tagging models' performance, we have constructed two high-quality POI tagging datasets from the real-world business scenario of Ali Fliggy. Upon the datasets, we conducted the extensive experiments to demonstrate our model's advantage over the baselines of uni-modality and multi-modality, and verify the effectiveness of important components in M3PT, including DIE, TIF and the contrastive learning strategy.Comment: Accepted by KDD 202

A Seismic Signal Denoising Method Based on Wavelet Comprehensive Threshold

The wavelet comprehensive threshold is used to inherit and develop the advantages of hard threshold and soft threshold denoised method. Based on the small wavelet coefficients of the noise signal and the large wavelet coefficients of the seismic signal, the simulation experiment of the Ricker signal and the noise reduction experiment is carried out. The simulation results show that the MSE of the wavelet comprehensive threshold is the closest to the original signal waveform after noise reduction, and the energy of the high frequency part of the waveform is reduced and the low frequency part is suppressed. Finally, the actual seismic waveform, for example, the noise reduction of the actual waveform can be the first time of the waveform, and the waveform of the effective signal energy, noise signal energy is suppressed

Fuzzy complex formation between the intrinsically disordered prothymosin α and the Kelch domain of Keap1 involved in the oxidative stress response.

Kelch-like ECH-associated protein 1 (Keap1) is an inhibitor of nuclear factor erythroid 2-related factor 2 (Nrf2), a key transcription factor for cytoprotective gene activation in the oxidative stress response. Under unstressed conditions, Keap1 interacts with Nrf2 in the cytoplasm via its Kelch domain and suppresses the transcriptional activity of Nrf2. During oxidative stress, Nrf2 is released from Keap1 and is translocated into the nucleus, where it interacts with the small Maf protein to initiate gene transcription. Prothymosin α (ProTα), an intrinsically disordered protein, also interacts with the Kelch domain of Keap1 and mediates the import of Keap1 into the nucleus to inhibit Nrf2 activity. To gain a molecular basis understanding of the oxidative stress response mechanism, we have characterized the interaction between ProTα and the Kelch domain of Keap1 by using nuclear magnetic resonance spectroscopy, isothermal titration calorimetry, peptide array analysis, site-directed mutagenesis, and molecular dynamic simulations. The results of nuclear magnetic resonance chemical shift mapping, amide hydrogen exchange, and spin relaxation measurements revealed that ProTα retains a high level of flexibility, even in the bound state with Kelch. This finding is in agreement with the observations from the molecular dynamic simulations of the ProTα-Kelch complex. Mutational analysis of ProTα, guided by peptide array data and isothermal titration calorimetry, further pinpointed that the region (38)NANEENGE(45) of ProTα is crucial for the interaction with the Kelch domain, while the flanking residues play relatively minor roles in the affinity of binding

Molecular effects of cancer-associated somatic mutations on the structural and target recognition properties of Keap1.

Kelch-like ECH-associated protein 1 (Keap1) plays an important regulatory role in the nuclear factor erythroid 2-related factor 2 (Nrf2)-dependent oxidative stress response pathway. It functions as a repressor of Nrf2, a key transcription factor that initiates the expression of cytoprotective enzymes during oxidative stress to protect cells from damage caused by reactive oxygen species. Recent studies show that mutations of Keap1 can lead to aberrant activation of the antioxidant pathway, which is associated with different types of cancers. To gain a mechanistic understanding of the links between Keap1 mutations and cancer pathogenesis, we have investigated the molecular effects of a series of mutations (G333C, G350S, G364C, G379D, R413L, R415G, A427V, G430C and G476R) on the structural and target recognition properties of Keap1 by using nuclear magnetic resonance (NMR) spectroscopy, circular dichroism (CD) and isothermal titration calorimetry (ITC). Depending on their locations in the protein, these mutations are found to exert differential effects on the protein stability and target binding. Together with the proposed hinge-and-latch mechanism of Nrf2-Keap1 binding in the literature, our results provide important insight into the molecular affect of different somatic mutations on Keap1\u27s function as an Nrf2 repressor