34 research outputs found

    A temporal Convolutional Network for EMG compressed sensing reconstruction

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    Electromyography (EMG) plays a vital role in detecting medical abnormalities and analyzing the biomechanics of human or animal movements. However, long-term EMG signal monitoring will increase the bandwidth requirements and transmission system burden. Compressed sensing (CS) is attractive for resource-limited EMG signal monitoring. However, traditional CS reconstruction algorithms require prior knowledge of the signal, and the reconstruction process is inefficient. To solve this problem, this paper proposed a reconstruction algorithm based on deep learning, which combines the Temporal Convolutional Network (TCN) and the fully connected layer to learn the mapping relationship between the compressed measurement value and the original signal, and it has been verified in the Ninapro database. The results show that, for the same subject, compared with the traditional reconstruction algorithms orthogonal matching pursuit (OMP), basis pursuit (BP), and Modified Compressive Sampling Matching Pursuit (MCo), the reconstruction quality and efficiency of the proposed method is significantly improved under various compression ratios (CR)

    ATPT: Automate Typhoon Contingency Plan Generation from Text

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    Artificial intelligence (AI) planning models play an important role in decision support systems for disaster management e.g. typhoon contingency plan development. However, constructing an AI planning model always requires significant amount of manual effort, which becomes a bottleneck to emergency response in a time-critical situation. In this demonstration, we present a framework of automating a domain model of planning domain definition language from natural language input through deep learning techniques. We implement this framework in a typhoon response system and demonstrate automatic generation of typhoon contingency plan from official typhoon plan documents

    Molecular identification and probiotic potential characterization of lactic acid bacteria isolated from the pigs with superior immune responses

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    Lactic acid bacteria (LAB) belong to a significant group of probiotic bacteria that provide hosts with considerable health benefits. Our previous study showed that pigs with abundant LAB had more robust immune responses in a vaccination experiment. In this study, 52 isolate strains were isolated from the pigs with superior immune responses. Out of these, 14 strains with higher antibacterial efficacy were chosen. We then assessed the probiotic features of the 14 LAB strains, including such as autoaggregation, coaggregation, acid resistance, bile salt resistance, and adhesion capability, as well as safety aspects such as antibiotic resistance, hemolytic activity, and the presence or absence of virulence factors. We also compared these properties with those of an opportunistic pathogen EB1 and two commercial probiotics (cLA and cLP). The results showed that most LAB isolates exhibited higher abilities of aggregation, acid and bile salt resistance, adhesion, and antibacterial activity than the two commercial probiotics. Out of the 14 strains, only LS1 and LS9 carried virulence genes and none had hemolytic activity. We selected three LAB strains (LA6, LR6 and LJ1) with superior probiotic properties and LS9 with a virulence gene for testing their safety in vivo. Strains EB1, cLA and cLP were also included as control bacteria. The results demonstrated that mice treated LAB did not exhibit any adverse effects on weight gain, organ index, blood immune cells, and ileum morphology, except for those treated with LS9 and EB1. Moreover, the antimicrobial effect of LR6 and LA6 strains was examined in vivo. The results indicated that these strains could mitigate the inflammatory response, reduce bacterial translocation, and alleviate liver, spleen, and ileum injury caused by Salmonella typhimurium infection. In addition, the LR6 treatment group showed better outcomes than the LA6 treatment group; treatment with LR6 substantially reduced the mortality rate in mice. The study results provide evidence of the probiotic properties of the LAB isolates, in particular LR6, and suggest that oral administration of LR6 could have valuable health-promoting benefits

    Observation of gravitational waves from the coalescence of a 2.5−4.5 M⊙ compact object and a neutron star

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    Search for eccentric black hole coalescences during the third observing run of LIGO and Virgo

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    Despite the growing number of confident binary black hole coalescences observed through gravitational waves so far, the astrophysical origin of these binaries remains uncertain. Orbital eccentricity is one of the clearest tracers of binary formation channels. Identifying binary eccentricity, however, remains challenging due to the limited availability of gravitational waveforms that include effects of eccentricity. Here, we present observational results for a waveform-independent search sensitive to eccentric black hole coalescences, covering the third observing run (O3) of the LIGO and Virgo detectors. We identified no new high-significance candidates beyond those that were already identified with searches focusing on quasi-circular binaries. We determine the sensitivity of our search to high-mass (total mass M>70 M⊙) binaries covering eccentricities up to 0.3 at 15 Hz orbital frequency, and use this to compare model predictions to search results. Assuming all detections are indeed quasi-circular, for our fiducial population model, we place an upper limit for the merger rate density of high-mass binaries with eccentricities 0<e≤0.3 at 0.33 Gpc−3 yr−1 at 90\% confidence level

    OCT and OCTA in dysthyroid optic neuropathy: a systematic review and meta-analysis

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    Purpose To explore the current research about the role of optical coherence tomography (OCT) and optical coherence tomography angiography (OCTA) in dysthyroid optic neuropathy (DON).Methods Studies in the literature that focused on OCT, OCTA and DON were retrieved by searching PubMed, EMBASE, Cochrane databases and Clinical Trial before 20 June 2023. The methodological quality was assessed using the Newcastle-Ottawa scale. The quantitative calculation was performed using Review Manager V.5.3.Results Twelve studies met the eligibility criteria and were included. DON group presented lower macular ganglion cell complex in the overall, superior and inferior hemifields compared with the non-DON group. Furthermore, the ganglion cell layer and inner plexiform layer in DON group was thinner in contrast to the non-DON group. The optic nerve head vessel density was lower in the DON group than that in the non-DON group. A reduction of radial peripapillary capillary vessel density could be seen in the DON group than the non-DON group in overall, inside disc, peripapillary, superior-hemifield, temporal and nasal. Besides, the macular superficial retinal capillary layer of non-DON and DON is lower than the healthy control group.Conclusions This study supported the potential value of OCT and OCTA metrics as novel biomarkers of DON. Ophthalmologists should comprehensively consider the retinal structure and microvasculature in dealing with DON.Ethics and dissemination This systematic review included data from published literature and was exempt from ethics approval. Results would be disseminated through peer-reviewed publication and presented at academic conferences engaging clinicians.PROSPERO registration number CRD42023414907

    Study on Aerodynamic Characteristics of A New Suspension Bridge with Twin-box Girder

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    This paper was reviewed and accepted by the APCWE-IX Programme Committee for Presentation at the 9th Asia-Pacific Conference on Wind Engineering, University of Auckland, Auckland, New Zealand, held from 3-7 December 2017

    Performance Analysis of Electromyogram Signal Compression Sampling in a Wireless Body Area Network

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    The rapid growth in demand for portable and intelligent hardware has caused tremendous pressure on signal sampling, transfer, and storage resources. As an emerging signal acquisition technology, compressed sensing (CS) has promising application prospects in low-cost wireless sensor networks. To achieve reduced energy consumption and maintain a longer acquisition duration for high sample rate electromyogram (EMG) signals, this paper comprehensively analyzes the compressed sensing method using EMG. A fair comparison is carried out on the performances of 52 ordinary wavelet sparse bases and five widely applied reconstruction algorithms at different compression levels. The experimental results show that the db2 wavelet basis can sparse EMG signals so that the compressed EMG signals are reconstructed properly, thanks to its low percentage root mean square distortion (PRD) values at most compression ratios. In addition, the basis pursuit (BP) reconstruction algorithm can provide a more efficient reconstruction process and better reconstruction performance by comparison. The experiment records and comparative analysis screen out the suitable sparse bases and reconstruction algorithms for EMG signals, acting as prior experiments for further practical applications and also a benchmark for future academic research

    Experimental Studies on VIV Countermeasures for Long-Span Suspension Bridge with Twin-box Girder

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    This paper was reviewed and accepted by the APCWE-IX Programme Committee for Presentation at the 9th Asia-Pacific Conference on Wind Engineering, University of Auckland, Auckland, New Zealand, held from 3-7 December 2017
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