Jul 2020 DOI 10.14302/issn.2643-2811.jmbr-20-3449
Stanley Raj A.Corresponding author
Department of Physics, Loyola College, Chennai, Tamilnadu- 600034, India.
Electrical resistivity method is often used to estimate the subsurface structure of the earth. Many inversion algorithms are available to estimate the subsurface features. However, predicting the exact parameter in the non-linear subsurface of the earth is difficult because of its complex composition. Soft computing tools can approximate the subsurface parameters more clearly. Each soft computing tool has certain advantages and disadvantages. A hybrid formation of algorithms will make the decision more appropriate than depending on a single tool. Here in our study the data obtained through Vertical Electrical Sounding has been used to determine the sub surface characteristics of earth viz., true resistivity and thickness. Artificial Neural Networks (ANN) requires certain optimizing procedures. Here in this paper, Genetic Algorithm (GA) is applied to optimize Artificial Neural Networks (ANN). This coupled approach is tested with the field data. Error percentage of algorithm nearly mimics the behavior of earth and is verified. The best performance result shows that this technique can be implemented to estimate the non-linear characteristics of the earth more noticeably.
Feb 2016 DOI 10.14302/issn.2575-7881.jdrr-15-849
BOULILA MoncefCorresponding author
Professor, Université de Sfax- Institut de l’Olivier- B.P. 14, 4061 Sousse Ibn Khaldoun, Tunisia.
Reverse Transcription Polymerase Chain Reaction (RT-PCR) using new designed primers pair for Heat Shock Protein70 homologue (HSP70h) of Olive leaf yellowing-associated virus revealed 667 amplified product of 10 olive accessions collected from various olive-growing regions in Tunisia. Amplicons were cloned and sequenced. The sequences were deposited in the international databases. Pairwise sequence comparisons among 10 Tunisian isolates along with a reference sequence (AJ440010) extracted from GenBank revealed a nucleotide identity of 86.06-99.40 and an amino acid similarity of 91.89-99.55. Sequence multiple alignments were searched for evidence of recombination using three methods, ie. Differences of Sums of Squares (DSS) implemented in TOPALi v2.5 software and Single Breakpoint (SBP) along with GARD, a genetic algorithm, both incorporated in HyPhy package. All used methods pointed out the presence of putative breaking points in partially sequenced HSP70h-coding gene. Since failing to account for recombination can mislead the phylogeny inference and can elevate the false positive error rate in positive selection assessment, the use of GARD resulted in the reconstruction of different phylogenies on the left as well as on the right sides of putative recombination breaking points, and the 11 accessions were distributed into at least three clusters compared to MEGA6 software which delineated only two clades. Nonetheless, by dividing the aligned sequences at breakpoints into separate sequence sets, MEGA6 delineated a clustering pattern different from the former two. As a result, recombination reshuffled the affiliation of the different accessions to the clusters. Analysis of selection pressures exerted on HSP70h encoded protein using different models (SLAC, IFEL, FEL, REL, PARRIS, FUBAR, MEME, GA Branch, and PRIME) taking into account recombination, and implemented in HyPhy package, revealed that it underwent predominantly purifying selection as confirmed by Tajima’s D, Fu and Li’s D and F tests, and SNAP algorithm. However, a few sites were also under positive selection as assessed by various models such as FEL, IFEL, REL, MEME, and PRIME.