Objective To update the meta-analysis comparing the effectiveness of oral appliance (OA) with continuous positive airway pressure (CPAP) in treating patients with obstructive sleep apnea (OSA). Methods PubMed, ISI Web of Knowledge, Ovid, EBSCO Dentistry & Oral Science Source, The Cochrane Library, and Embase database were searched for RCTs until 23 May 2017. Meta-analyses were performed using RevMan 5.3. Results Sixteen RCTs were included. Compared with OA, CPAP significantly decreased AHI, min SaO2, ARI, ESS (p < 0.05), with no significant difference in REM%, FOSQ, BP (p ≥ 0.05). OA significantly improved REM% in the severe groups and ESS in the adjustable OA group (p < 0.05). OA shared greater preference. Conclusion Even though CPAP can better decrease the severity of OSA, more patients opted for OA, which showed better results in severe patients, especially adjustable OA.
Micro-expressions (MEs) are the expressions of real emotion in people’s heart. It usually happens when people want to hide their true emotions. Through the study of MEs, we can correctly speculate on the inner activities of the expressors, which has important application value in the fields of criminal investigation, arrest, psychotherapy, education and teaching. At present, more and more people are paying attention to the research of ME recognition. People try to detect MEs by faster algorithms, but the recognition process is affected by many factors, so it is necessary to optimize related technologies as soon as possible to achieve higher accuracy. Therefore, this paper analyzes the application of ME recognition and related algorithms, and puts forward the development prospects.
<p style='text-indent:20px;'>In this paper, we propose a restoration model for image degraded by different kinds of blur and mixing Gaussian-impulse noise. Our model consist of a nonconvex Exponential-Type (ET) function, a <inline-formula><tex-math id="M1">\begin{document}$ L_{2} $\end{document}</tex-math></inline-formula>-norm data-fitting term and a fractional-order Besov norm as the regularization term. We employ the proximal linearized minimization (PLM) algorithm and alternating direction method of multipliers (ADMM) algorithm to solve our proposed minimization model, convergence analysis is carried out. The experimental outcomes demonstrate that the restored images by our proposed method are better than those existing relative methods in terms of PSNR, SSIM values and visual quality.</p>
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