To achieve safe security to transfer data from the sender to receiver, cryptography is one way that is used for such purposes. However, to increase the level of data security, DNA as a new term was introduced to cryptography. The DNA can be easily used to store and transfer the data, and it becomes an effective procedure for such aims and used to implement the computation. A new cryptography system is proposed, consisting of two phases: the encryption phase and the decryption phase. The encryption phase includes six steps, starting by converting plaintext to their equivalent ASCII values and converting them to binary values. After that, the binary values are converted to DNA characters and then converted to their equivalent complementary DNA sequences. These DNA sequences are converted to RNA sequences. Finally, the RNA sequences are converted to the amino acid, where this sequence is considered as ciphertext to be sent to the receiver. The decryption phase also includes six steps, which are the same encryption steps but in reverse order. It starts with converting amino acid to RNA sequences, then converting RNA sequences to DNA sequences and converting them to their equivalent complementary DNA. After that, DNA sequences are converted to binary values and to their equivalent ASCII values. The final step is converting ASCII values to alphabet characters that are considered plaintext. For evaluation purposes, six text files with different sizes have been used as a test material. Performance evaluation is calculated based on encryption time and decryption time. The achieved results are considered as good and fast, where the encryption and decryption times needed for a file with size of 1k are equal to 2.578 ms and 2.625 ms respectively, while the encryption and decryption times for a file with size of 20k are equal to 268.422 ms and 245.469 ms respectively.
Two series of bent and liner core mesogen containing 1,2,4-traizole ring [VI]a,g and series were synthesized by many steps starting from esterification of isophthalic acid and terephathalic acid with methanol to yield diester compound [I]a,b which was converted to their acid hydrazide [II]a,b and the acid hydrazide reacted with ammonium thiocyanate or diester reacted with thiosemicarbazide to yield compounds [III]a,b. Then cyclization by 4% NaOH to yielded 1,2,4 traizole-3- thiol compounds [IV]a,b , afterword adding hydrazine hydrate to yield compounds [V]a,b. These compounds condensated with different substituted aldehyde to give new Schiff bases[VI]a,b ,[VII]a,b . Also , reaction acid hydrazide [II]a,b with aldehyde [VII] to yielded Schif
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Background: Enforcement of sustainable and green chemistry protocols has seen colossal surge in recent times, the development of an effective, eco-friendly, simple and novel methodologies towards the synthesis of valuable synthetic scaffolds and drug intermediates. Recent advances in technology have now a more efficient means of heating reactions that made microwave energy. Efforts to synthesize novel heterocyclic molecules of biological importance are in continuation. Microwave irradiation is well known to promote the synthesis of a variety of organic and inorganic compounds. The aim of current study was to conceivea mild base mediated preparation of novel Schiff base of 2-Acetylpheno with trimethoprim drug (H2TPBD) and its complexes w
... Show MoreThe precise classification of DNA sequences is pivotal in genomics, holding significant implications for personalized medicine. The stakes are particularly high when classifying key genetic markers such as BRAC, related to breast cancer susceptibility; BRAF, associated with various malignancies; and KRAS, a recognized oncogene. Conventional machine learning techniques often necessitate intricate feature engineering and may not capture the full spectrum of sequence dependencies. To ameliorate these limitations, this study employs an adapted UNet architecture, originally designed for biomedical image segmentation, to classify DNA sequences.The attention mechanism was also tested LONG WITH u-Net architecture to precisely classify DNA sequences
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Abstract
The present study investigates the effect of acetic acid on corrosion behavior and its potential of hydrothermally sealed anodized AA2319-Al-alloys. Anodizing treatment was performed in stagnant phosphoric acid electrolyte with or without addition of acetic acid. Hydrothermal sealing was carried out in boiling water for each anodized specimen. The open circuit potential of the unsealed and sealed anodized samples was examined using open circuit potential measurement for the purpose of starting in scanning polarization diagrams. The potentiostatic polarization technique measurements were performed to assess corrosion behavior and sealing quality (i.e., degree of sealing) of
... Show MoreDNA, as the basis of every living cell, is one of the most important and influential scientific discoveries. This research aims to identify and compare the organizational DNA to the leadership practices of school principals in the Sultanate of Oman and to reveal the similarity between principals’ leadership practices and the structure of DNA. In addition, it intends to identify any statistically significant differences between the responses of the participants due to the study variables: gender, job title and experience. A questionnaire was designed and data were collected from a randomly selected sample composed of (100) teachers in the Sultanate of Oman. The study found limitless diversity in the characteristics of DNA of leadership
... Show MoreNowadays, internet security is a critical concern; the One of the most difficult study issues in network security is "intrusion detection". Fight against external threats. Intrusion detection is a novel method of securing computers and data networks that are already in use. To boost the efficacy of intrusion detection systems, machine learning and deep learning are widely deployed. While work on intrusion detection systems is already underway, based on data mining and machine learning is effective, it requires to detect intrusions by training static batch classifiers regardless considering the time-varying features of a regular data stream. Real-world problems, on the other hand, rarely fit into models that have such constraints. Furthermor
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