Association rules mining (ARM) is a fundamental and widely used data mining technique to achieve useful information about data. The traditional ARM algorithms are degrading computation efficiency by mining too many association rules which are not appropriate for a given user. Recent research in (ARM) is investigating the use of metaheuristic algorithms which are looking for only a subset of high-quality rules. In this paper, a modified discrete cuckoo search algorithm for association rules mining DCS-ARM is proposed for this purpose. The effectiveness of our algorithm is tested against a set of well-known transactional databases. Results indicate that the proposed algorithm outperforms the existing metaheuristic methods.

Most heuristic search method's performances are dependent on parameter choices. These parameter settings govern how new candidate solutions are generated and then applied by the algorithm. They essentially play a key role in determining the quality of the solution obtained and the efficiency of the search. Their fine-tuning techniques are still an on-going research area. Differential Evolution (DE) algorithm is a very powerful optimization method and has become popular in many fields. Based on the prolonged research work on DE, it is now arguably one of the most outstanding stochastic optimization algorithms for real-parameter optimization. One reason for its popularity is its widely appreciated property of having only a small number of par

Background: The Epstein-Barr virus (EBV) relates to the torch virus family and is believed to have a substantial impact on mortality and perinatal events, as shown by epidemiological and viral studies. Moreover, there have been documented cases of EBV transmission occurring via the placenta. Nevertheless, the specific location of the EBV infection inside the placenta remains uncertain. Methods: The genomic sequences connected to the latent EBV gene and the levels of lytic EBV gene expression in placental chorionic villous cells are examined in this work. A total of 86 placentas from patients who had miscarriage and 54 placentas from individuals who had successful births were obtained for analysis. Results: The research employed QPCR to dete

This study aimed to detect Anaplasma phagocytophilum in horses through hematological and molecular tests. The 16S rRNA gene of the Anaplasma phagocytophilum parasite was amplified by polymerase chain reaction (PCR), then sequenced, and subjected to phylogenetic analysis to explore "Equine Granulocytic Anaplasmosis" (EGA) infection in three important gathering race horses areas in Baghdad governorate, Iraq. Blood samples were obtained from 160 horses of varying ages, three breeds, and both sexes, between January and December 2021. Prevalence and risk variables for anaplasmosis were analyzed using statistical odds ratio and chi-square tests. Results demonstrated that clinical anaplasmosis symptoms comprised jaundice, wei

The present study aimed to isolate and diagnose mesenchymal stem cells derived from human bone that is the source generating cells that are the best types of treatment for tissue diseases.
Cells were isolated from the back bone of the human pelvis, separated using density gradual sedimentation method and then the cells were grown on the culture media RPMI-1640 \ 20% FBS.
To detect the purity of cells that have been isolated and have been transplanted immune use the method using CD44 (mesenchymal stem cells marker) CD43, a specific marker for hematopoietic cells Nestin, (the neurons private marker).
The present study has shown that mesenchymal cells that have been isolated and expanded in this experiment has reached up 99.7% for

Biometrics represent the most practical method for swiftly and reliably verifying and identifying individuals based on their unique biological traits. This study addresses the increasing demand for dependable biometric identification systems by introducing an efficient approach to automatically recognize ear patterns using Convolutional Neural Networks (CNNs). Despite the widespread adoption of facial recognition technologies, the distinct features and consistency inherent in ear patterns provide a compelling alternative for biometric applications. Employing CNNs in our research automates the identification process, enhancing accuracy and adaptability across various ear shapes and orientations. The ear, being visible and easily captured in

Cladosporium sp. plays an important role in human health, it is one of the pathogenic fungi which cause allergy and asthma and most frequently isolated from airborne spores.  In this study, a couple of universal PCR primers were designed to identify the pathogenic fungi Cladosporium sp. according to conserved region 5.8S, 18S and 28S subunit ribosomal RNA gene in Cladosporium species. In silico RFLP-PCR were used to identify twenty-four Cladosporium strains. The results showed that the universal primer has the specificity to amplify the conserved region in 24 species as a band in virtual agarose gel. They also showed that the RFLP method is able to identify three Cladosporium spe