A hospital-based survey of Kawasaki disease was performed in all 45 hospitals with in-patient beds Beijing during the 5-year period from 2000 through 2004. total 1107 patients were enrolled, an annual incidence varying 40.9 to 55.1 per 100,000 children <5 years age. The coronary complications 20.6% acute stage, and 6.9% 1-2 month follow-up.

Abstract To improve the product quality and process reliability in semiconductor manufacturing, it is of great significance to detect defect wafer map recognize pattern. With increase complexity chip design manufacturing processes, a variety mixed defects appear more frequently, recognition (WMMDR) has become focus many scholars. Most current methods based on deep learning are complex, do not uniformly solve problems weak features, overlapping occlusion, inter-class similarity maps....

Objectives: To investigate the incidence of adjacent segment degeneration (ASD) following extreme lateral interbody fusion (XLIF) and identify risk factors for early ASD after XLIF. Methods: A retrospective study was conducted, including patients diagnosed with lumbar spinal stenosis who underwent XLIF at Tianjin Hospital between July 2019 December 2022 were followed-up least one year. Preoperative final follow-up MRI X-ray examination performed all to evaluate status segments. According...

Controversy exists as to whether elevated loop gain is a cause or consequence of obstructive sleep apnea (OSA). Upper airway surgery commonly performed in Asian patients with OSA who have failed positive pressure therapy and are thought anatomical predisposition OSA. We hypothesized that high would decrease following surgical treatment due reduced severity.Polysomnography was preoperatively postoperatively assess severity 30 Chinese participants underwent upper surgery. Loop calculated using...

Deep learning has proven itself to be able reduce the scanning time of Magnetic Resonance Imaging (MRI) and improve image reconstruction quality since it was introduced into Compressed Sensing MRI (CS-MRI). However, requirement using large, high-quality, patient-based datasets for network training procedures is always a challenge in clinical applications. In this paper, we propose novel deep based compressed sensing MR method that does not require any pre-training procedure or dataset,...

Convolutional neural networks (CNNs) have exhibited commendable performance in the hyperspectral images (HSIs) classification task with manually annotated limited available training data for supervision. The accurate of pixel-wise land covers using traditional CNNs is often hampered by presence wrong (noisy) labels and can easily be overfitted to label noises. However, on noisy labeled inevitably suffers from degradation since tend overfit To overcome this problem, we propose a lightweight...

Ship surveillance by remote sensing technology has become a valuable tool for protecting marine environments. In recent years, the successful launch of advanced synthetic aperture radar (SAR) sensors that have high resolution and multipolarimetric modes enabled researchers to use SAR imagery not only ship detection but also category recognition. A hierarchical recognition scheme is proposed. The complementary information obtained from used improve both precision accuracy. stage, three-class...

To investigate the therapeutic effect of Vericiguat combined with "new quadruple" drugs on patients heart failure (HF).

Feature extraction is a key factor to detect pesticides using terahertz spectroscopy. Compared traditional methods, deep learning able obtain better insights into complex data features at high levels of abstraction. However, reports about the application in THz spectroscopy are rare. The main limitation analyse insufficient samples. In this study, we proposed WGAN-ResNet method, which combines two networks, Wasserstein generative adversarial network (WGAN) and residual neural (ResNet),...

In order to diagnose nonlinear and non-stationary fault signals in bearings, a new method is presented based on the ensemble empirical decomposition (EEMD) fuzzy c-means (FCM) clustering algorithm. At first, bearing were decomposed using EEMD intrinsic mode functions (IMF) produced. Second energy ratios of these IMFs computed taken as characteristic parameters for FCM Then was conducted classify into different classes. Finally, basis preceding classification results, we diagnosed through...

Envelope modified versions of the empirical mode decomposition (EMD) method such as B-spline interpolation-based EMD (B-EMD) and cardinal spline (C-EMD) have been proposed recently for purpose improving its effectiveness. To shed further light on their performance, behaviours these EMD-type methods in presence white Gaussian noises are investigated this study based extensive numerical experiments. Similarly to method, it turns out that envelope also act filter banks essentially. However,...

A cytosolic manganese superoxide dismutase gene (Es-cMnSOD) was cloned from the Chinese mitten crab Eriocheir sinensis, using reverse transcription-polymerase chain reaction and rapid amplification of cDNA ends.The open reading frame Es-cMnSOD is 867 bp in length encodes a 288-amino acid protein without signal peptide.The calculated molecular mass translated 31.43kDa, with an estimated isoelectric point 6.30.The deduced amino sequence has similarities 90, 89, 84, 87, 81% to those white...

In this study, the authors propose a novel method, namely Toeplitz-based singular value decomposition (or TL-SVD for short) reconstruction and basis function construction of electromagnetic interference (EMI) source signals. Given specific EMI signal, they first construct Toeplitz type data matrix. By applying (SVD) to constructed matrix, obtain set values, which are further divided into two parts, corresponding clear noisy components input signals, respectively. The de-noised signal can...

Objective This study aims to evaluate the combination of genioglossus (GG) activity and anatomical characteristics in predicting outcomes velopharyngeal surgery patients with obstructive sleep apnea (OSA). Study Design Case series planned data collection. Setting Sleep medical center. Subjects Methods Forty OSA underwent overnight polysomnography synchronous electromyography (GGEMG) using intraoral electrodes. The upper airway anatomy was evaluated by 3‐dimensional computed tomography OSA....

Abstract Human–robot collaboration has been widely used in postdisaster investigation and rescue. team training is a good way to improve the rescue efficiency safety; two common methods, namely, procedural cross‐training, are explored this study. Currently, relatively few studies have impact of cross‐training on human–robot tasks. Cross‐training will be novel most rescuers as such, an evaluation comparison with more conventional warranted. This study investigated effects these methods...

Nowadays, the issue of Electromagnetic Compatibility is great importance and urgency. In this paper, we propose a novel hybrid automatic identification system for power quality disturbances, which lays foundations further analyzing electromagnetic compatibility. Specifically, firstly extract features by using FFT envelope detection method. Then utilize attribute weighted artificial immune evolutionary Classifier (AWAIEC) classification disturbance events. Experimental results have shown that...

Deep learning has shown potential in significantly improving performance for undersampled magnetic resonance (MR) image reconstruction. However, one challenge the application of deep to clinical scenarios is requirement large, high-quality patient-based datasets network training. In this paper, we propose a novel learning-based method MR reconstruction that does not require pre-training procedure and datasets. The proposed reference-driven using wavelet sparsity-constrained prior (RWS-DIP)...