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Alzheimer's disease (AD) is the most common cognitive disorder in the elderly. Its main clinical manifestations are cognitive decline (C), behavioral and psychological symptoms (B), and a decline in the activities of daily living (A), also known as ABC symptoms. Early identification and evaluation of ABC symptoms are helpful for establishing the accurate diagnosis, comprehensive treatment, and prognosis of AD. To guide Chinese clinical practice for optimization of the comprehensive management of AD, in 2018, The Academy of Cognitive Disorder of China gathered 22 neurologists and gerontologists in China to build a consensus on the comprehensive management of AD. Based on a review of the evidence, the consensus summarizes the pathogenesis, pathological changes, clinical manifestations, evaluation, diagnosis, drug and non-drug treatment, and patient care for AD. Focus group discussion was used to establish a flowchart of comprehensive ABC management for AD patients. The new consensus provides a feasible AD management process for clinicians.

In this paper, we present a new version of the famous Rudin-Osher-Fatemi (ROF) model to restore image.The key point of the model is that it could reconstruct images with blur and non-uniformly distributed noise. We develop this approach by adding several statistical control parameters to the cost functional, and these parameters could be adaptively determined by the given observed image. In this way, we could adaptively balance the performance of the fit-to-data term and the regularization term. The Numerical experiments have demonstrated the significant effectiveness and robustness of our model in restoring blurred images with mixed Gaussian noise or salt-and-pepper noise.