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The importance of identifying network traffic abnormalities in cybersecurity cannot be emphasized enough, particularly considering the growing frequency and complexity of computer network assaults. With the emergence of new Internet-related technology, there is a corresponding increase in complex assaults. A significant difficulty is dictionary-based brute-force assaults (BFA), which need efficient real-time detection and mitigation techniques. This study explores the detection of SSH and FTP brute-force attacks via the use of the primary objective of our study is to use the machine learning methodology for the identification and detection of SSH and FTP brute-force assaults. Employing many classifiers enables a pretty comprehensive examination of the effectiveness of machine learners in spotting brute force attacks on SSH and FTP. Brute-force attacks are a widely used and perilous technique for acquiring usernames and passwords. Utilizing ethical hacking is a commendable method to assess the impact of a brute-force attack. This article explores several defense tactics and methodologies for using brute-force attacks. The advantages and disadvantages of many defense techniques are listed, along with details on the kind of attack that is most straightforward to recognize. we made use of machine learning (ML) classifiers: Naive Bayes (NB), decision Tree (DT), random forest (RF) Logistic Regression (LG), Quadratic Discriminant Analysis (QDA), Stochastic Gradient Descent (SGD), Linear Discriminant Analysis (LDA), Multi-Layer Perceptron (MLP), we determined that the Random Forest (RF) algorithm achieved the highest level with an accuracy of 99.9%.

Mucuna (Mucuna bracteata) is a cover crop for young plants in oil palm plantations. However, it has a very low germination rate due to its hard outer shell and fungi infestation after germination. Thus, this study was conducted to determine the effectivity of mechanical treatment combined with 15-min of Dithane M-45 treatment to improve the germination rate of Mucuna’s seed and its seedling growth. The experiment was performed with the combination of two factors: mechanical treatment and Dithane M-45 (0.00 g/L, 0.05 g/Lg, 0.10 g/L and 0.15 g/L) in pentaplicate for each group. The seeds were sowed on wet cotton, and the data was analyzed using ANOVA (α = 0.05) followed by DMRT (α = 0.05). The shell nicking seed followed by a 0.10 g/L of Dithane M-45 treatment resulted in the best germination rate (88 ± 9.1%), the fastest germination speed (6.29 ± 0.65 %), the shortest mean germination time (4.25 ± 0.87 days), the longest shoot, and the highest of fresh and dry biomass for both shoot and root of the seedlings. Therefore, the shell nicking and fungicide immersion before sowing the seeds could improve Mucuna's germination and seedling growth.

Studies to evaluate new genetic forms of spring barley were carried out in 2020-2022. in the conditions of the center of the European part of Russia (Ryazan region) on the following varieties: Znatny, Pamyati Chepeleva (Russia); Kufal, Reider (Belarus); KVS Harris, KVS Vermont, Bente, Ellinor (Germany); LG Nabucco, Rapid (France); Laureate (Switzerland), regionalized in the period 2018-2020. It was established that the varieties Znatny - 6.38 t/ha, Ellinor - 6.02 t/ha and Kufal - 5.98 t/ha had the highest average yield. According to the length of the spike (≥8.0 cm), the varieties Bente and Znatny stood out. It has been established that the varieties Pamyati Chepeleva and Laureate have the highest productive bushiness (≥4.0), the varieties Kufal, Reider, Bente have a high grain size (≥50.0 g). According to a number of statistical indicators for assessing adaptability, the following varieties were identified: in terms of the level of yield and plasticity of the variety - Znatny and Ellinor (more than 100.0%); according to the coefficient of adaptability - Znatny, Kufal, KVS Harris, KVS Vermont, Ellinor and Rapid (K.A.> 1.0); in terms of phenotypic stability (1.22…1.58) – Bente, KVS Harris, Noble, Ellinor and Rapid; according to the level of homeostasis (> 0.30) - Bente, Noble and Ellinor; by the minimum value of the range of yield (

This is the first study to assess antiviral activity against human influenza virus A/Aichi/2/68 and bird influenza virus A/chicken/Kurgan/05/2005 and phytochemical characteristics of an ethanol extract of Cacalia hastata L. from wild populations growing in the vicinity of Tomsk, Russia (mixed forest). A log10 neutralization index—an indicator of inhibition of virus replication by the extract from C. hastata leaves—was ≤2 lg for each influenza virus. The extract reduced the infectivity of the human influenza virus by 1.5-fold and that of the avian influenza virus by 1.7-fold. The phytochemical characterization of C. hastata (its various organs) showed that the largest amount of the tested biologically active substances is present in leaves and rhizomes.