Optimization for a New XY Positioning Mechanism by Artificial Neural Network-Based Metaheuristic Algorithms.

This paper devotes a new method in modeling and optimizing to handle the optimization of the XY positioning mechanism. The fitness functions and constraints of the mechanism are formulated via proposing a combination of artificial neural network (ANN) and particle swarm optimization (PSO) methods. Next, the PSO is hybridized with the grey wolf optimization, namely PSO-GWO, which is applied to three scenarios in handling the single objective function. In order to search the multiple functions for the mechanism, the multiobjective optimization genetic algorithm (MOGA) is applied to the last scenario. The achieved results showed that the fitness functions are well-formulated using the PSO-based ANN method. In the scenario 1, the stroke achieved by the PSO-GWO (1852.9842 µm) is better than that gained from the GWO (1802.8087 µm). In the scenarios 2, the stress gained from the PSO-GWO (243.3183 MPa) is lower than that achieved from the GWO (245.0401 MPa). In the scenario 3, the safety factor retrieved from the PSO-GWO (1.9767) is greater than that achieved from the GWO (1.9278). In the scenario 4, by using MOGA, the optimal results found that the stroke is about (1741.3 µm) and the safety factor is 1.8929. The prediction results are well-fitted with the numerical and experimental verifications. The results of this paper are expected to facilitate the synthesis and analysis of compliant mechanisms and related engineering designs.

Molecular characterization of hepatitis B virus in Bangladesh reveals a highly recombinant population.

The natural history and treatment outcome of hepatitis B viruses (HBV) infection is largely dependent on genotype, subgenotype, and the presence or absence of virulence associated mutations. We have studied the prevalence of genotype and subgenotype as well as virulence and drug resistance associated mutations and prevalence of recombinant among HBV from Bangladesh. A prospective cross-sectional study was conducted among treatment naïve chronic HBV patients attending at Bangabandhu Sheikh Mujib Medical University, Dhaka, Bangladesh for HBV viral load assessment between June and August 2015. Systematical selected 50% of HBV DNA positive patients (every second patient) were enrolled. Biochemical and serological markers for HBV infection and whole genome sequencing (WGS) was performed on virus positive sample. Genotype, subgenotype, virulence, nucleos(t)ide analogue (NA) resistance (NAr) mutations, and the prevalence of recombinant isolates were determined. Among 114 HBV DNA positive patients, 57 were enrolled in the study and 53 HBV WGS were generated for downstream analysis. Overall, 38% (22/57) and 62% (35/57) of patients had acute and chronic HBV infections, respectively. The prevalence of genotypes A, C, and D was 18.9% (10/53), 45.3% (24/53), and 35.8% (19/53), respectively. Among genotype A, C and D isolates subgenotype A1 (90%; 9/10), C1 (87.5%; 21/24) and D2 (78.9%; 15/19) predominates. The acute infection, virulence associated mutations, and viral load was higher in the genotype D isolates. Evidence of recombination was identified in 22.6% (12/53) of the HBV isolates including 20.0% (2/10), and 16.7% (4/24) and 31.6% (6/19) of genotype A, C and D isolates, respectively. The prevalence of recombination was higher in chronic HVB patients (32.2%; 10/31 versus 9.1%; 2/22); p<0.05. NAr mutations were identified in 47.2% (25/53) of the isolates including 33.9% novel mutations (18/53). HBV genotype C and D predominated in this population in Bangladesh; a comparatively high prevalence of recombinant HBV are circulating in this setting.