Fifty snails of Paropeas achatinaceum specimens were collected and classified from four areas in Baghdad-Iraq from the period between June and July, 2017. The snails were divided into two groups (each group contain 25 snails). Two environment conditions were used in this study. Natural environment considered as control and experimental environment contains Citrus sinensis (L.) roots as snail’s source food. The comparison result between snail weights in the nature and experimental environment was not significant (0.497, 95% confidence interval [CI] 0.01209–0.02309). Also, the comparison between snail weights in the nature environment and the food mean weight was significant (0.014, 95% confidence interval [CI] 0.00591-0.04109), while the comparison between snail weights in the experimental environment and the food mean weight was significant (0.005, 95% confidence interval [CI] 0.01141-0.04659). Sequencing of COI gene of this specimen was done to find the similarity with the same gene sequences database which published in National Center of Biotechnology Information (NCBI). Polymerase chain reaction (PCR) technique revealed presence one band for part of mt DNA COI gene with 710 bp. The sequencing results revealed a high similarity (98%) with the Paropeas achatinaceum (accession number MF415354.1; specimen collected from Sri Lanka), which published in NCBI. The sequence data was submitted in the NCBI and the accession number of the COI gene sequences was MG747646.1.
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XML is being incorporated into the foundation of E-business data applications. This paper addresses the problem of the freeform information that stored in any organization and how XML with using this new approach will make the operation of the search very efficient and time consuming. This paper introduces new solution and methodology that has been developed to capture and manage such unstructured freeform information (multi information) depending on the use of XML schema technologies, neural network idea and object oriented relational database, in order to provide a practical solution for efficiently management multi freeform information system.
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This article proposes a new strategy based on a hybrid method that combines the gravitational search algorithm (GSA) with the bat algorithm (BAT) to solve a single-objective optimization problem. It first runs GSA, followed by BAT as the second step. The proposed approach relies on a parameter between 0 and 1 to address the problem of falling into local research because the lack of a local search mechanism increases intensity search, whereas diversity remains high and easily falls into the local optimum. The improvement is equivalent to the speed of the original BAT. Access speed is increased for the best solution. All solutions in the population are updated before the end of the operation of the proposed algorithm. The diversification f
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KE Sharquie, AA Al-Nuaimy, FA Al-Shimary, Saudi medical journal, 2005 - Cited by 20
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The convergence speed is the most important feature of Back-Propagation (BP) algorithm. A lot of improvements were proposed to this algorithm since its presentation, in order to speed up the convergence phase. In this paper, a new modified BP algorithm called Speeding up Back-Propagation Learning (SUBPL) algorithm is proposed and compared to the standard BP. Different data sets were implemented and experimented to verify the improvement in SUBPL.
Laboratory studies were conducted at the biological control unit, college of Agriculture, University of Baghdad to evaluate some biological aspects of the predator Chilocorus bipustulatus (Coleoptera: Coccinellidae), which is considered one of the most important predators on many insect pests, especially the scale insect, Parlatoria blanchardi, (Homoptera: Diaspididae) on date palms. The results showed that biological parameters of the predator were varied according to different degree of temperature. Egg incubation period was significantly different and reached to 7.5 and 5.44 day at 25 and 30°C respectively, Fertility was the same 100% at both temperature degrees. Larval growth periods were 17.41 and 16.12 day as well as the mortality du
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