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The rapid development of many open source and commercial image editing software makes the authenticity of the digital images questionable. Copy-move forgery is one of the most widely used tampering techniques to create desirable objects or conceal undesirable objects in a scene. Existing techniques reported in the literature to detect such tampering aim to improve the robustness of these methods against the use of JPEG compression, blurring, noise, or other types of post processing operations. These post processing operations are frequently used with the intention to conceal tampering and reduce tampering clues. A robust method based on the color moments and other five image descriptors is proposed in this paper. The method divides the image into fixed size overlapping blocks. Clustering operation divides entire search space into smaller pieces with similar color distribution. Blocks from the tampered regions will reside within the same cluster since both copied and moved regions have similar color distributions. Five image descriptors are used to extract block features, which makes the method more robust to post processing operations. An ensemble of deep compositional pattern-producing neural networks are trained with these extracted features. Similarity among feature vectors in clusters indicates possible forged regions. Experimental results show that the proposed method can detect copy-move forgery even if an image was distorted by gamma correction, addictive white Gaussian noise, JPEG compression, or blurring.

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Background: Parkinson’s disease (PD) is the most common neurodegenerative disease closely related to the immune system, among whose prodromes constipation is a representative symptom. Recent Randomized Controlled Trials (RCTs) have proved that probiotics can be used to effectively treat PD constipation, but the results are inconsistent. We performed a meta-analysis to assess the efficacy and safety of probiotic therapy on Parkinson’s constipation.Methods: Questions about the research focus were constructed based on the Participants, Intervention, Comparison and Outcomes (PICO) Criteria. We searched electronic databases such as PubMed, Web of Science, EMBASE, Scopus, EBSCO, Cochrane and Google Scholar until March 2022 for eligible literatures. Our primary endpoints were stool frequency, stool consistency, the number of laxatives uses, UPDRS-III scores and adverse events.Results: 12 eligible studies (n = 818 patients) met the inclusion and endpoint criteria. Meta-analysis results showed that constipation symptoms were improved after probiotic treatment, including an increased stool frequency (WMD = 0.94, 95% CI:0.53 to 1.34; OR = 3.22, 95% CI:1.97–5.29), an improved stool consistency (WMD = 1.46, 95% CI:0.54–2.37), a reduced use of laxatives (WMD = −0.72, 95%CI: −1.04 to−0.41), and also a reduced Parkinson’s UPDRS-III score (WMD = −6.58, 95%CI: −12.02 to −1.14); there was no significant difference in total adverse events (OR = 0.82, 95%CI:0.39–1.72).Conclusion: Our analysis suggests that probiotics can be used to improve the constipation and motor symptoms for patients with Parkinson’s constipation, possibly by reducing the inflammatory response and improving gut-brain axis neuron function, whose safety also proved to be good.

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