Search

Due to the complex underwater environment and the selective absorption and scattering effect of water on light waves, underwater images often suffer from issues such as low contrast, color distortion, and blurred details. This paper presents a stable and effective algorithm for enhancing underwater images to address these challenges. Firstly, an improved color correction algorithm based on the gray world and minimum information loss is employed to remove the blue-green bias present in the images. Secondly, a contrast enhancement algorithm is based on the guided filter and wavelet decomposition to make the texture details of the image clearer. Then, the normalized weight map of the image is obtained to carry out multi-scale fusion. Finally, the fused image is applied to perform the multi-scale decomposition. The experimental results show that the algorithm proposed in this paper can correct the image color deviation, improve the image contrast and enhance the image details. [ABSTRACT FROM AUTHOR]

There have been reports of association between psoriasis and psychological illnesses. Nevertheless, it is not easy to draw conclusions with high quality causality from conventional observational studies. The objective of this study was to evaluate the causality of psoriasis and psychological illnesses. All summary-level data from genome-wide association studies for psoriasis and psychological illnesses were collected from Neale Lab and MRC Integrative Epidemiology Unit. Bidirectional Mendelian randomization analysis was performed to determine the random orientation with an independent genetic variation. The main estimated effects are derived using Inverse-Variance Weighted, weighted median, and MR Egger methods. Multiple data sets were validated against each other, and a series of sensitivity studies were conducted to ensure the reliability of the results. Mendelian randomization analysis revealed a causal effect of psoriasis [odds ratio (OR) 1·34, 95% confidence interval (CI) 1·21–1·46, P < 0.001; and OR 1.28, CI 1.17–1.39, P < 0.001] on psychological illnesses, and vice versa (OR 1.23, CI 1.14–1.31, P < 0.001; and OR 1.21, CI 1.11–1.31, P < 0.001). The results were supported by a series of sensitivity analyses. The findings of this Mendelian randomization study support a causal effect between psoriasis and psychological illnesses, and vice versa. [ABSTRACT FROM AUTHOR]

For the bearing fault diagnosis in small sample cases, a new model for signal denoising and entropy feature fusion (EFF) based on the wild horse optimizer (WHO) optimized variational mode decomposition (VMD) and correlation coefficient weight threshold (CCWT) is proposed (WHO–VMD–CCWT–EFF). For signal denoising, we first take the power spectrum entropy as the fitness function, and the WHO is used to optimize VMD parameters. Secondly, IMFs with correlation coefficient values less than 0.2 are removed and the correlation coefficient values as weights are applied to the corresponding IMF components, and then reconstruct them. Then, the refined composite multiscale dispersion entropy (RCMDE), refined composite multiscale fluctuation dispersion entropy (RCMFDE), refined composite multivariate generalized multiscale fuzzy entropy (RCmvMFE), refined composite multivariate generalized multiscale sample entropy (RCmvMSE), and multiscale permutation entropy (MPE) of the signal are calculated and fused. Finally, the Fisher discriminant classifier is used as the model for fault diagnosis. The proposed model achieves an accuracy of over 99% in 12 single working conditions and 30 multiple working conditions experiments using the case western reserve university (CWRU) dataset and the Paderborn dataset. Compared with existing feature fusion methods, the WHO–VMD–CCWT–EFF model only integrates five selected features, and can achieve accurate diagnosis of bearing faults in small sample experiments with 42 different artificial and real damages. This indicates that the model has good generalization ability between different datasets and working conditions. [ABSTRACT FROM AUTHOR]

The global k-means algorithm is an incremental approach to clustering that dynamically adds one cluster center at a time through a deterministic global search procedure from suitable initial positions, and employs k-means to minimize the sum of the intra-cluster variances. However the global k-means algorithm sometimes results singleton clusters and the initial positions sometimes are bad, after a bad initialization, poor local optimal can be easily obtained by k-means algorithm. In this paper, we modified the global k-means algorithm to eliminate the singleton clusters at first, and then we apply MinMax k-means clustering error method to global k-means algorithm to overcome the effect of bad initialization, proposed the global Minmax k-means algorithm. The proposed clustering method is tested on some popular data sets and compared to the k-means algorithm, the global k-means algorithm and the MinMax k-means algorithm. The experiment results show our proposed algorithm outperforms other algorithms mentioned in the paper. [ABSTRACT FROM AUTHOR]

Rationale: With the development of various imaging techniques, the deformation-based morphometry (DBM) method provides an objective automatic examination of the whole brain. Objectives: This study aims to assess the abnormalities in the brains of first-episode schizophrenia (FES) patients treated with quetiapine using another advanced nonrigid registration method, hierarchical attribute matching mechanism for elastic registration, through the application of DBM in the entire brain. Methods: Thirty FES patients and 30 normal controls were grouped by age and handedness and subjected to magnetic resonance imaging examination. The patients had relatively short durations of untreated psychosis (DUP; 6.4 ± 5.2 months), and only a single antipsychotic drug, quetiapine (dosage, 200 ± 75 mg), was used for treatment. Statistically significant changes in regional volume were analyzed via DBM. In addition, a voxel-wise analysis of correlations between the duration of treatment or dosage and volume was also performed. Results: Compared with control subjects, FES patients showed contracted regions located in Brodmann area (BA) 42 and BA 19. By contrast, expanded regions were observed in BA 38, BA 21, BA 6 and 8, and left cerebellum. A negative correlation was observed between dosage and volume in the hippocampus, while a positive correlation was found in the caudate. Meanwhile, a negative correlation was observed between duration of treatment and volume in BA 38. Conclusion: Both regional volume reductions and increases were detected in the brains of FES patients treated with quetiapine compared with healthy control subjects. Such differences may be partially relevant to dosage and treatment duration in clinic. [ABSTRACT FROM AUTHOR]

Based on the fact that many infectious diseases exhibit periodic fluctuations and there is a saturated phenomenon during disease treatment, we study an SIR model with periodic incidence rate and saturated treatment function. Firstly, we find that the basic reproduction number less than 1 cannot insure the global stability of disease-free equilibrium and it needs to add other conditions. Moreover, we establish sufficient conditions for the multiplicity of positive periodic solutions. We also apply the numerical method to confirm theoretical results and show the stability of the periodic solutions. We observe that there are two periodic solutions in the system where one is stable and the other one is unstable. These results will provide some guidance for control measures of disease. [ABSTRACT FROM AUTHOR]

Microwave ablation therapy has become an important method for tumor treatment in recent years. The temperature and the coagulation region need real-time noninvasive monitoring to ensure the safety and effectiveness during the treatment. The authors reviewed the ultrasonic monitoring methods for tumor microwave ablation therapy both at home and abroad. In addition, the authors also prospected this technique in the future. [ABSTRACT FROM AUTHOR]

ADIPOQ gene polymorphisms have been indicated to be associated with hypertension; however, published studies have reported inconsistent results. Eligible studies were retrieved by searching the PubMed, Embase and China National Knowledge Infrastructure databases. The case group consisted of patients with hypertension, and the control group consisted of subjects with normal blood pressure. Based on eleven published articles, involving 4837 cases and 5618 controls, the pooled results from rs2241766 polymorphism showed increased risk in the allelic model (G VS T: OR = 1.16, 95%CI = 1.06-1.27), recessive model (GG VS GT + TT: OR = 1.34, 95%CI = 1.10-1.63), dominant model (GG + GT VS TT: OR = 1.15, 95%CI = 1.02-1.30) and homozygote model (GG VS TT: OR = 1.38, 95%CI = 1.21-1.69). In addition, rs266729 polymorphism showed increased risk for hypertension in the recessive model (GG VS GC + CC: OR = 1.43, 95%CI = 1.02-2.01). In the Caucasian subgroup, rs1501299 polymorphism showed decreased risk of hypertension in the allelic model (T VS G: OR = 0.75, 95%CI = 0.58-0.97), dominant model (TT + TG VS GG: OR = 0.83, 95%CI = 0.71-0.98) and heterozygote model (TG VS GG: OR = 0.82, 95%CI = 0.68-0.99). The rs2241766 polymorphism was associated with a significant increase in hypertension risk based on our analysis. Moreover, an increased risk of rs266729 in hypertension patients was also detected. Our meta-analysis suggests that the rs1501299 polymorphism may play a protective role in hypertension in Caucasian subgroup; however, this finding requires further study. [ABSTRACT FROM AUTHOR]