85 research outputs found

    Low-dimensional Denoising Embedding Transformer for ECG Classification

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    The transformer based model (e.g., FusingTF) has been employed recently for Electrocardiogram (ECG) signal classification. However, the high-dimensional embedding obtained via 1-D convolution and positional encoding can lead to the loss of the signal's own temporal information and a large amount of training parameters. In this paper, we propose a new method for ECG classification, called low-dimensional denoising embedding transformer (LDTF), which contains two components, i.e., low-dimensional denoising embedding (LDE) and transformer learning. In the LDE component, a low-dimensional representation of the signal is obtained in the time-frequency domain while preserving its own temporal information. And with the low dimensional embedding, the transformer learning is then used to obtain a deeper and narrower structure with fewer training parameters than that of the FusingTF. Experiments conducted on the MIT-BIH dataset demonstrates the effectiveness and the superior performance of our proposed method, as compared with state-of-the-art methods.Comment: To appear at ICASSP 202

    Induced 3-Hom-Lie superalgebras

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    We construct 3-Hom-Lie superalgebras on a commutative Hom-superalgebra by means of involution and even degree derivation. We construct a representation of induced 3-Hom-Lie superalgebras by means of supertrace

    Efficacy and safety of traditional Chinese medicine adjuvant therapy for severe pneumonia: evidence mapping of the randomized controlled trials, systematic reviews, and meta-analyses

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    Background and Objective: Severe pneumonia is a critical respiratory disease with high mortality. There is insufficient evidence on the efficacy and safety of traditional Chinese medicine (TCM) adjuvant therapy for severe pneumonia. This study aims to identify, describe, assess, and summarize the currently available high-quality design evidence on TCM adjuvant therapy for severe pneumonia to identify evidence gaps using the evidence mapping approach.Methods: Systematic searches were performed on English and Chinese online databases (PubMed, EMBASE, Cochrane Library, Web of Science, CNKI, WanFang Data, CQVIP, and SinoMed) to identify papers from inception until August 2023 for inclusion into the review. Randomized controlled trials (RCTs), systematic reviews (SRs), and meta-analyses concerning TCM adjuvant therapy for severe pneumonia or its complications in adults were included. The risk of bias in RCTs was evaluated by using the Cochrane Handbook ROB tool. The Assessment of Multiple Systematic Reviews 2 (AMSTAR-2), the Risk of Bias in Systematic Review (ROBIS) tool, and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system were used to assess the methodological quality, risk of bias, and evidence quality of SRs or meta-analyses, respectively. Then, a bubble plot was designed to visually display information in four dimensions.Results: A total of 354 RCTs and 17 SRs or meta-analyses met the inclusion criteria. The published RCTs had several flaws, such as unreasonable design, limited sample size, insufficient attention to non-drug therapy studies and syndrome differentiation, improper selection or use of outcome indicators, and failure to provide high-quality evidence. Sixteen SRs or meta-analyses of methodological quality scored “Critically Low” confidence. Twelve SRs or meta-analyses were rated as “High Risk.” Most outcomes were rated as “Low” evidence quality. We found that TCM combined with conventional treatment could improve the clinical total effective rate and the TCM syndromes efficacy. The combined approach could also shorten mechanical ventilation time, infection control time, and length of hospital and ICU stay; significantly reduce temperature, respiratory rate, heart rate, white blood cell counts, levels of C-reactive protein, procalcitonin, blood inflammatory factors, bacteriological response, and D-dimer; decrease CPIS, APACHE II score, and PSI score; improve pulmonary imaging features, arterial blood gas indicators (including arterial oxygen pressure, arterial oxygen saturation, and oxygen index), and lung function (including forced vital capacity and forced expiratory volume in the first second) for severe pneumonia compared with conventional treatment only (p < 0.05). There was no significant difference in adverse reactions and incidence of adverse events (p > 0.05). In addition, compared with conventional treatment only, most SRs or meta-analyses concluded that TCM combined with conventional treatment was “Beneficial” or “Probably beneficial.”Conclusion: TCM combined with conventional treatment had advantages in efficacy, clinical signs, laboratory results, and life quality outcomes of severe pneumonia, with no difference in safety outcomes compared with conventional treatment only. QingJin Huatan decoction is the most promising target, and Xuanbai Chengqi decoction has a “Probably beneficial” conclusion. XueBiJing injection and TanReQing injection are two commonly used Chinese herbal injections for treating severe pneumonia, and both are “Probably beneficial.” However, there was a need for multicenter RCTs with large sample sizes and high methodological quality in the future. In addition, the methodological design and quality of SRs or meta-analyses should be improved to form high-quality, evidence-based medical evidence and provide evidence for the effectiveness and safety of TCM adjuvant therapy for severe pneumonia

    Laser Grinding of Single-Crystal Silicon Wafer for Surface Finishing and Electrical Properties

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    In this paper, we first report the laser grinding method for a single-crystal silicon wafer machined by diamond sawing. 3D laser scanning confocal microscope (LSCM), X-ray diffraction (XRD), scanning electron microscope (SEM), X-ray photoelectron spectroscopy (XPS), laser micro-Raman spectroscopy were utilized to characterize the surface quality of laser-grinded Si. Results show that SiO2 layer derived from mechanical machining process has been efficiently removed after laser grinding. Surface roughness Ra has been reduced from original 400 nm to 75 nm. No obvious damages such as micro-cracks or micro-holes have been observed at the laser-grinded surface. In addition, laser grinding causes little effect on the resistivity of single-crystal silicon wafer. The insights obtained in this study provide a facile method for laser grinding silicon wafer to realize highly efficient grinding on demand

    Laser Grinding of Single-Crystal Silicon Wafer for Surface Finishing and Electrical Properties

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    In this paper, we first report the laser grinding method for a single-crystal silicon wafer machined by diamond sawing. 3D laser scanning confocal microscope (LSCM), X-ray diffraction (XRD), scanning electron microscope (SEM), X-ray photoelectron spectroscopy (XPS), laser micro-Raman spectroscopy were utilized to characterize the surface quality of laser-grinded Si. Results show that SiO2 layer derived from mechanical machining process has been efficiently removed after laser grinding. Surface roughness Ra has been reduced from original 400 nm to 75 nm. No obvious damages such as micro-cracks or micro-holes have been observed at the laser-grinded surface. In addition, laser grinding causes little effect on the resistivity of single-crystal silicon wafer. The insights obtained in this study provide a facile method for laser grinding silicon wafer to realize highly efficient grinding on demand

    Energy Performance Assessment of the Container Housing in Subtropical Region of China upon Future Climate Scenarios

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    Being continuously abandoned in huge amounts year-round by freight industry, shipping containers meet increasing regenerative utility in forms of temporary buildings, small public facilities, etc., especially in fast-developing countries with large populations and high living intensities like China. Although recycled containers have been nicely entitled with green building visions, their characterized inferior thermal properties (low inertia, poor insulation, etc.) when compared to conventional building forms and materials will greatly hinder their energy-saving potential, especially under the serious future extreme climate expectations. It therefore becomes particularly necessary to uncover the actual energy and thermophysical behaviors of the container building typology, upon extreme future climate scenarios targeting zero carbon forms for small-scale and temporary buildings in the upcoming future. In reference to existing data, this study made reasonable predictions of future extreme climate conditions (2050 and 2080), employing the Morphing method, and examined the cooling energy performances of the typical container housing in a subtropical climate through dynamic simulations. The energy-saving effectiveness of key design variables including insulation types, thicknesses, window opening areas and air infiltration rates has been validated and quantitatively revealed for such a building typology among the tested hot summer and warm winter region. Results imply that the additional energy burden brought by future extreme weather conditions cannot be ignored. The heat gains from envelopes and hot air infiltration are both key design factors of cooling energy increments for such building types upon future extreme climates. Compared with expanded pearl- and vermiculite-type insulation materials, thinner (70~90 mm) plastics and mineral wool-type ones have better energy-saving performance and therefore are worth consideration. High air infiltration rates and window openings in eastern or western orientations shall be carefully selected. The research outcomes can provide key references for design decisions made for the energy-efficient and low-carbon design of the container building typology among subtropical zones, or similar climate regions in response to future climate conditions

    Utility-Based Divisible Sensing Task Scheduling in Wireless Sensor Networks

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    This paper presents a tractable optimization strategies of sensing workload scheduling in wireless sensor networks using Divisible Load Theory (DLT). Because of the limited battery power of sensors, it is desirable that the sensor network can complete a task as quickly as possible. Given a task, each source node processes an appropriate fraction of the entire workload and then transmits the result to the sink node via a set of routing nodes. Two representative network models are presented to illustrate how the workload is scheduled among the sensor nodes so that the finish time of the workload is minimized. Furthermore, we present the energy model for nodes in a two-level hierarchical network topology. Finally, simulation results are presented to demonstrate the effects of selected system parameters such as the number of sensor nodes, measurement, processing, and communication speed on the performance of the sensor network
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