Identification of the exact location of an exon in a DNA sequence is an important research area of bioinformatics. The main issues of the previous signal processing techniques are accuracy and robustness for the exact locating of exons. To address the mentioned issues, in this study, a method has been proposed based on deep learning. The proposed method includes a new preprocessing, a new mapping method, and a multi-scale modified and hybrid deep neural network. The proposed preprocessing method enriches the network to accept and encode genes at any length in a new mapping method. The proposed multi-scale deep neural network uses a combination of an embedding layer, a modified CNN, and an LSTM network. In this study, HMR195, BG570, and F56F11.4 datasets have been used to compare this work with previous studies. The accuracies of the proposed method have been 0.982, 0.966, and 0.965 on HMR195, BG570, and F56F11.4 databases, respectively. The results reveal the superiority and effectiveness of the proposed hybrid multi-scale CNN-LSTM network.

The ant Cataglyphis bazoftensis Khalili-Moghadam Salata & Borowiec, 2021 has been recently described in Iran. Here, new materials of C. bazoftensis were collected from five new localities in Chaharmahal and Bakhtiari provinces, Iran. All the specimens examined were morphologically consistent with the description of C. bazoftensis. At the molecular level, based on a phylogenetic trees obtained from the mitochondrial Cytochrome C oxidase subunit I gene (COI), C. bazoftensis appears as the sister taxon of Cataglyphis kurdistanica Pisarski, 1965, separated from each other by a genetic distance of 9. 79 %

This text carries out some ideas about exact and d P− exact sequences of transformation semi groups. Some theorems like the short five lemma (Lemma 1.3 and Lemma 2.3) are valid here as in exact sequences of R − modules.

We present a cost-optimal and adaptive parallel algorithm for generating t-ary trees with P-sequences. The computational model employed in this algorithm is an exclusive read exclusive write with a shared memory single instruction multiple data computer. Our parallel algorithm is the first designed P-sequence generation on this model.Prior to the discussion of this parallel algorithm, a new sequential algorithm for generation of t-ary trees with Per sequence in O(1) constant average time per sequence is presented.

Given an i.i.d. sequence of n letters from a finite alphabet, we consider the length of the longest run of any letter. In the equiprobable case, results for this run turn out to be closely related to the well-known results for the longest run of a given letter. For coin-tossing, tail probabilities are compared for both kinds of runs via Poisson approximation