An adaptation reference-point-based multiobjective evolutionary algorithm

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.It is well known that maintaining a good balance between convergence and diversity is crucial to the performance of multiobjective optimization algorithms (MOEAs). However, the Pareto front (PF) of multiobjective optimization problems (MOPs) affects the performance of MOEAs, especially reference point-based ones. This paper proposes a reference-point-based adaptive method to study the PF of MOPs according to the candidate solutions of the population. In addition, the proportion and angle function presented selects elites during environmental selection. Compared with five state-of-the-art MOEAs, the proposed algorithm shows highly competitive effectiveness on MOPs with six complex characteristics

A dynamic multiobjective evolutionary algorithm based on a dynamic evolutionary environment model

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Traditional dynamic multiobjective evolutionary algorithms usually imitate the evolution of nature, maintaining diversity of population through different strategies and making the population track the Pareto optimal solution set efficiently after the environmental change. However, these algorithms neglect the role of the dynamic environment in evolution, leading to the lacking of active guieded search. In this paper, a dynamic multiobjective evolutionary algorithm based on a dynamic evolutionary environment model is proposed (DEE-DMOEA). When the environment has not changed, this algorithm makes use of the evolutionary environment to record the knowledge and information generated in evolution, and in turn, the knowledge and information guide the search. When a change is detected, the algorithm helps the population adapt to the new environment through building a dynamic evolutionary environment model, which enhances the diversity of the population by the guided method, and makes the environment and population evolve simultaneously. In addition, an implementation of the algorithm about the dynamic evolutionary environment model is introduced in this paper. The environment area and the unit area are employed to express the evolutionary environment. Furthermore, the strategies of constraint, facilitation and guidance for the evolution are proposed. Compared with three other state-of-the-art strategies on a series of test problems with linear or nonlinear correlation between design variables, the algorithm has shown its effectiveness for dealing with the dynamic multiobjective problems

A rapid and efficient method for the extraction and identification of menaquinones from Actinomycetes in wet biomass

Abstract Background Menaquinones are constituents of prokaryote cell membranes where they play important functions during electron transport. Menaquinone profiles are strongly recommended for species classification when proposing a new Actinomycetes taxon. Presently, the most widely used methods to determine menaquinones are based on freeze-dried cells. Taxonomic research in our lab has revealed that menaquinone concentrations are low for some species of the genus Microbacterium, leading to difficulties in identifying menaquinones. Results Menaquinones extracted using the novel lysozyme-chloroform-methanol (LCM) method were comparable in quality to those obtained using the Collins method, the most widely used method. All tested strains extracted via the LCM method showed higher concentrations of menaquinones than those extracted via the Collins method. For some Microbacterium strains, the LCM method exhibited higher sensitivity than the Collins method, and more trace menaquinones were detected with the LCM method than the Collins method. In addition, LCM method is faster than the Collins method because it uses wet cells. Conclusion The LCM method is a simple, rapid and efficient technique for the extraction and identification of menaquinones from Actinomycetes

An infeasible solutions diversity maintenance epsilon constraint handling method for evolutionary constrained multiobjective optimization

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.It is well known that it is very difficult to solve constrained multiobjective optimization problems. Such problems not only need to optimize the objective function but also need to consider the constraints. The epsilon constraint handling method is commonly used, which releases the degree of constraint violations by defining a gradually decayed epsilon. However, for the solutions whose overall constraint violations degree is greater than epsilon, the original epsilon constraint handling method cannot guarantee the diversity of solutions and only constraint violations are considered. To solve this issue, this paper proposed an infeasible solutions diversity maintenance strategy for solutions whose constraint violations degree is greater than epsilon. The experimental results show that our proposed algorithm is very competitive with other state-of-the-art algorithms for constrained multiobjective optimization problems

A reconstruction method for cross-cut shredded documents based on the extreme learning machine algorithm

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Reconstruction of cross-cut shredded text documents (RCCSTD) has important applications for information security and judicial evidence collection. The traditional method of manual construction is a very time-consuming task, so the use of computer-assisted efficient reconstruction is a crucial research topic. Fragment consensus information extraction and fragment pair compatibility measurement are two fundamental processes in RCCSTD. Due to the limitations of the existing classical methods of these two steps, only documents with specific structures or characteristics can be spliced, and pairing error is larger when the cutting is more fine-grained. In order to reconstruct the fragments more effectively, this paper improves the extraction method for consensus information and constructs a new global pairwise compatibility measurement model based on the extreme learning machine algorithm. The purpose of the algorithm’s design is to exploit all available information and computationally suggest matches to increase the algorithm’s ability to discriminate between data in various complex situations, then find the best neighbor of each fragment for splicing according to pairwise compatibility. The overall performance of our approach in several practical experiments is illustrated. The results indicate that the matching accuracy of the proposed algorithm is better than that of the previously published classical algorithms and still ensures a higher matching accuracy in the noisy datasets, which can provide a feasible method for RCCSTD intelligent systems in real scenarios

Niche-based and angle-based selection strategies for many-objective evolutionary optimization

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.It is well known that balancing population diversity and convergence plays a crucial role in evolutionary many-objective optimization. However, most existing multiobjective evolutionary algorithms encounter difficulties in solving many-objective optimization problems. Thus, this paper suggests niche-based and angle-based selection strategies for many-objective evolutionary optimization. In the proposed algorithm, two strategies are included: niche-based density estimation strategy and angle-based selection strategy. Both strategies are employed in the environmental selection to eliminate the worst individual from the population in an iterative way. To be specific, the former estimates the diversity of each individual and finds the most crowded area in the population. The latter removes individuals with weak convergence in the same niche. Experimental studies on several well-known benchmark problems show that the proposed algorithm is competitive compared with six state-of-the-art many-objective algorithms. Moreover, the proposed algorithm has also been verified to be scalable to deal with constrained many-objective optimization problems

Complete genome sequence of a novel Prescottella sp. R16 isolate from deep-sea sediments in the western Pacific

Prescottella, a distinct genus separate from Rhodococcus, has garnered attention for its adaptability and ecological versatility. In this study, a Gram-stain positive and ovoid-rod shaped the actinobacterium strain R16 was isolated from deep-sea sediment (with a depth of 6,310 m) in the Western Pacific. On the basis of 16S rRNA gene sequence analysis, average nucleotide identity and phylogenomic analysis, strain R16 clearly represents a novel species within the genus Prescottella. Genomic analyses indicate Prescottella sp. R16 contains a circular chromosome of 4,531,251 bp with an average GC content of 68.9%, 4,208 protein-coding genes, 51 tRNA genes, and 12 rRNA operons. Additionally, four CRISPRs and 24 genomic islands are also identified. The presence of rich categories related to catalytic activity, membrane part and metabolic process highlights their involvement in cellular component, biological process, and molecular function. The genome sequence of strain R16 also revealed the presence of 13 putative biosynthetic gene clusters for secondary metabolites, including those for ε-Poly-L-lysine, ectoine, heterobactin, isorenieratene and corynecin, suggesting its potential for antibiotic production and warranting further exploration

DataSheet2_Complete genome sequence of a novel Prescottella sp. R16 isolate from deep-sea sediments in the western Pacific.xlsx

Prescottella, a distinct genus separate from Rhodococcus, has garnered attention for its adaptability and ecological versatility. In this study, a Gram-stain positive and ovoid-rod shaped the actinobacterium strain R16 was isolated from deep-sea sediment (with a depth of 6,310 m) in the Western Pacific. On the basis of 16S rRNA gene sequence analysis, average nucleotide identity and phylogenomic analysis, strain R16 clearly represents a novel species within the genus Prescottella. Genomic analyses indicate Prescottella sp. R16 contains a circular chromosome of 4,531,251 bp with an average GC content of 68.9%, 4,208 protein-coding genes, 51 tRNA genes, and 12 rRNA operons. Additionally, four CRISPRs and 24 genomic islands are also identified. The presence of rich categories related to catalytic activity, membrane part and metabolic process highlights their involvement in cellular component, biological process, and molecular function. The genome sequence of strain R16 also revealed the presence of 13 putative biosynthetic gene clusters for secondary metabolites, including those for ε-Poly-L-lysine, ectoine, heterobactin, isorenieratene and corynecin, suggesting its potential for antibiotic production and warranting further exploration.</p

New Monoterpenoids and Polyketides from the Deep-Sea Sediment-Derived Fungus Aspergillus sydowii MCCC 3A00324

Chemical study of the secondary metabolites of a deep-sea-derived fungus Aspergillus sydowii MCCC 3A00324 led to the isolation of eleven compounds (1&ndash;11), including one novel (1) and one new (2) osmane-related monoterpenoids and two undescribed polyketides (3 and 4). The structures of the metabolites were determined by comprehensive analyses of the NMR and HRESIMS spectra, in association with quantum chemical calculations of the 13C NMR, ECD, and specific rotation data for the configurational assignment. Compound 1 possessed a novel monoterpenoid skeleton, biogenetically probably derived from the osmane-type monoperpenoid after the cyclopentane ring cleavage and oxidation reactions. Additionally, compound 3 was the first example of the &alpha;-pyrone derivatives bearing two phenyl units at C-3 and C-5, respectively. The anti-inflammatory activities of 1&ndash;11 were tested. As a result, compound 6 showed potent inhibitory nitric oxide production in lipopolysaccharide (LPS)-activated BV-2 microglia cells with an inhibition rate of 94.4% at the concentration of 10 &micro;M. In addition, a plausible biosynthetic pathway for 1 and 2 was also proposed

DataSheet1_Complete genome sequence of a novel Prescottella sp. R16 isolate from deep-sea sediments in the western Pacific.docx

Prescottella, a distinct genus separate from Rhodococcus, has garnered attention for its adaptability and ecological versatility. In this study, a Gram-stain positive and ovoid-rod shaped the actinobacterium strain R16 was isolated from deep-sea sediment (with a depth of 6,310 m) in the Western Pacific. On the basis of 16S rRNA gene sequence analysis, average nucleotide identity and phylogenomic analysis, strain R16 clearly represents a novel species within the genus Prescottella. Genomic analyses indicate Prescottella sp. R16 contains a circular chromosome of 4,531,251 bp with an average GC content of 68.9%, 4,208 protein-coding genes, 51 tRNA genes, and 12 rRNA operons. Additionally, four CRISPRs and 24 genomic islands are also identified. The presence of rich categories related to catalytic activity, membrane part and metabolic process highlights their involvement in cellular component, biological process, and molecular function. The genome sequence of strain R16 also revealed the presence of 13 putative biosynthetic gene clusters for secondary metabolites, including those for ε-Poly-L-lysine, ectoine, heterobactin, isorenieratene and corynecin, suggesting its potential for antibiotic production and warranting further exploration.</p