Homogeneous Nature of Malaysian Marine Fish Epinephelus fuscoguttatus (Perciformes; Serranidae): Evidence Based on Molecular Markers,Morphology and Fourier Transform Infrared Analysis

Taxonomic confusion exists within the genus Epinephelus due to the lack of morphological specializations and the overwhelming number of species reported in several studies. The homogenous nature of the morphology has created confusion in the Malaysian Marine fish species Epinephelus fuscoguttatus and Epinephelus hexagonatus. In this study, the partial DNA sequence of the 16S gene and mitochondrial nucleotide sequences of two gene regions, Cytochrome Oxidase Subunit I and III were used to investigate the phylogenetic relationship between them. In the phylogenetic trees, E. fuscoguttatus was monophyletic with E. hexagonatus species and morphology examination shows that no significant differences were found in the morphometric features between these two taxa. This suggests that E. fuscoguttatus is not distinguishable from E. hexagonatus species, and that E. fuscoguttatus have been identified to be E. hexagonatus species is likely attributed to differences in environment and ability to camouflage themselves under certain conditions. Interestingly, this finding was also supported by Principal Component Analysis on Attenuated Total Reflectance–Fourier-transform Infrared (ATR-FTIR) data analysis. Molecular, morphological and meristic characteristics were combined with ATR-FTIR analysis used in this study offer new perspectives in fish species identification. To our knowledge, this is the first report of an extensive genetic population study of E. fuscoguttatus in Malaysia and this understanding will play an important role in informing genetic stock-specific strategies for the management and conservation of this highly valued fish.     

Molecular Systematics of Polygonum minus Huds. Based on ITS Sequences

Plastid trnL-trnF and nuclear ribosomal ITS sequences were obtained from selected wild-type individuals of Polygonum minus Huds. in Peninsular Malaysia. The 380 bp trnL-trnF sequences of the Polygonum minus accessions were identical. Therefore, the trnL-trnF failed to distinguish between the Polygonum minus accessions. However, the divergence of ITS sequences (650 bp) among the Polygonum minus accessions was 1%, indicating that these accessions could be distinguished by the ITS sequences. A phylogenetic relationship based on the ITS sequences was inferred using neighbor-joining, maximum parsimony and Bayesian inference. All of the tree topologies indicated that Polygonum minus from Peninsular Malaysia is unique and different from the synonymous Persicaria minor (Huds.) Opiz and Polygonum kawagoeanum Makino.     

Modified 2 Satisfiability Reverse Analysis Method via Logical PermutationOperator

The effectiveness of the logic mining approach is strongly correlated to the quality of the induced logical representation that represent the behaviour of the data. Specifically, the optimum induced logical representation indicates the capability of the logic mining approach in generalizing the real datasets of different variants and dimensions. The main issues with the logic extracted by the standard logic mining techniques are lack of interpretability and the weakness in terms of the structural and arrangement of the 2 Satisfiability logic causing lower accuracy. To address the issues, the logical permutation serves as an alternative mechanism that can enhance the probability of the 2 Satisfiability logical rule becoming true by utilizingthedefinitive finite arrangement of attributes. This work aims to examine and analyze the significant effect of logical permutation on the performance of data extraction ability of the logic mining approach incorporated with the recurrent discrete Hopfield Neural Network. Based on the theory, the effect of permutation and associate memories in recurrent Hopfield Neural Network will potentially improve the accuracy of the existing logic mining approach. To validate the impact of the logical permutation on the retrieval phase of the logic mining model, the proposed work is experimentally tested on a different class of the benchmark real datasets ranging from the multivariate and time-series datasets. The experimental results show the significant improvement in the proposed logical permutation-based logic mining according to the domains such as compatibility, accuracy, and competitiveness as opposed to the plethora of standard 2 Satisfiability Reverse Analysis methods.