Enhanced Slime Mould Algorithm for Multilevel Thresholding Image Segmentation Using Entropy Measures.

Image segmentation is a fundamental but essential step in image processing because it dramatically influences posterior image analysis. Multilevel thresholding image segmentation is one of the most popular image segmentation techniques, and many researchers have used meta-heuristic optimization algorithms (MAs) to determine the threshold values. However, MAs have some defects; for example, they are prone to stagnate in local optimal and slow convergence speed. This paper proposes an enhanced slime mould algorithm for global optimization and multilevel thresholding image segmentation, namely ESMA. First, the Levy flight method is used to improve the exploration ability of SMA. Second, quasi opposition-based learning is introduced to enhance the exploitation ability and balance the exploration and exploitation. Then, the superiority of the proposed work ESMA is confirmed concerning the 23 benchmark functions. Afterward, the ESMA is applied in multilevel thresholding image segmentation using minimum cross-entropy as the fitness function. We select eight greyscale images as the benchmark images for testing and compare them with the other classical and state-of-the-art algorithms. Meanwhile, the experimental metrics include the average fitness (mean), standard deviation (Std), peak signal to noise ratio (PSNR), structure similarity index (SSIM), feature similarity index (FSIM), and Wilcoxon rank-sum test, which is utilized to evaluate the quality of segmentation. Experimental results demonstrated that ESMA is superior to other algorithms and can provide higher segmentation accuracy.

Differential blood lipid-lowering effects of alkylsulfonated chitosan of different molecular weights in Syrian hamsters in vivo.

This study investigated the effects of alkylsulfonated chitosan of different molecular weights on intestinal lipid absorption, blood lipid profiles and circulating adhesion molecules. Syrian hamsters were fed an AIN-93G-based high­fat diet (HFD) and were orally administered 5 or 10 mg/kg BW of oligomer (6 kDa) chitosan (OC), low­molecular-weight (70 kDa) chitosan (LMC) or high­molecular-weight (200 kDa) chitosan (HMC) four times per week for 12 weeks. Animals receiving 2.5 mg/kg BW lovastatin (LOVA) served as a positive control. The blood lipid profiles of these control animals revealed that all chitosans and LOVA significantly decreased total triglyceride, total cholesterol, low­density lipoprotein (LDL)-cholesterol and very­low­density lipoprotein (VLDL)-cholesterol levels in a dose­dependent manner compared to the HFD-fed controls (P<0.05). The blood lipid lowering effectiveness of the three chitosans followed the order of LMC>OC>HMC. Hamsters receiving 5 and 10 mg/kg LMC (P<0.05) exhibited an increase in fecal fat content. Immunoblot assay revealed that acyl­coenzyme A:cholesterol acyltransferase-2 (ACAT-2) expression was suppressed in all chitosan-fed animals compared to the HFD-fed controls (P<0.05). These results suggest that chitosan effectively decreases blood lipid content, and its effectiveness depends on the molecular size of chitosan. The hypolipidemic effect of chitosan is partly attributed to its suppression of intestinal lipid absorption and hepatic ACAT-2 expression.