The Industrial Revolution 4.0 began with the breakthrough technological advances in 5G, and artificial intelligence has innovatively transformed the manufacturing industry from digitalization and automation to the new era of smart factories. A smart factory can do not only more than just produce products in a digital and automatic system, but also is able to optimize the production on its own by integrating production with process management, service distribution, and customized product requirement. A big challenge to the smart factory is to ensure that its network security can counteract with any cyber attacks such as botnet and Distributed Denial of Service, They are recognized to cause serious interruption in production, and consequently economic losses for company producers. Among many security solutions, botnet detection using honeypot has shown to be effective in some investigation studies. It is a method of detecting botnet attackers by intentionally creating a resource within the network with the purpose of closely monitoring and acquiring botnet attacking behaviors. For the first time, a proposed model of botnet detection was experimented by combing honeypot with machine learning to classify botnet attacks. A mimicking smart factory environment was created on IoT device hardware configuration. Experimental results showed that the model performance gave a high accuracy of above 96%, with very fast time taken of just 0.1 ms and false positive rate at 0.24127 using random forest algorithm with Weka machine learning program. Hence, the honeypot combined machine learning model in this study was proved to be highly feasible to apply in the security network of smart factory to detect botnet attacks.
Thiamine, or vitamin B1 plays an indispensable role as a cofactor in crucial metabolic reactions including glycolysis, pentose phosphate pathway and the tricarboxylic acid cycle in all living organisms. Thiamine has been shown to play a role in plant adaptation toward biotic and abiotic stresses. The modulation of thiamine biosynthetic genes in oil palm seedlings was evaluated in response to root colonization by endophytic Hendersonia toruloidea. Seven-month-old oil palm seedlings were inoculated with H. toruloidea and microscopic analyses were performed to visualize the localization of endophytic H. toruloidea in oil palm roots. Transmission electron microscopy confirmed that H. toruloidea colonized cortical cells. The expression of thiamine biosynthetic genes and accumulation of total thiamine in oil palm seedlings were also evaluated. Quantitative real-time PCR was performed to measure transcript abundances of four key thiamine biosynthesis genes (THI4, THIC, TH1, and TPK) on days 1, 7, 15, and 30 in response to H. toruloidea colonization. The results showed an increase of up to 12-fold in the expression of all gene transcripts on day 1 post-inoculation. On days 7, 15, and 30 post-inoculation, the relative expression levels of these genes were shown to be downregulated. Thiamine accumulation was observed on day 7 post-colonization and subsequently decreased until day 30. This work provides the first evidence for the enhancement of thiamine biosynthesis by endophytic colonization in oil palm seedlings.
Clinacanthus nutans has had a long history of use in folk medicine in Malaysia and Southeast Asia; mostly in the relief of inflammatory conditions. In this study, we investigated the effects of different extracts of C. nutans upon lipopolysaccharide (LPS) induced inflammation in order to identify its mechanism of action. Extracts of leaves and stem bark of C. nutans were prepared using polar and non-polar solvents to produce four extracts, namely polar leaf extract (LP), non-polar leaf extract (LN), polar stem extract (SP), and non-polar stem extracts (SN). The extracts were standardized by determining its total phenolic and total flavonoid contents. Its anti-inflammatory effects were assessed on LPS induced nitrite release in RAW264.7 macrophages and Toll-like receptor (TLR-4) activation in TLR-4 transfected human embryonic kidney cells (HEK-Blue(TM)-hTLR4 cells). The levels of inflammatory cytokines (TNF-α, IFN-γ, IL-1β, IL-6, IL-12p40, and IL-17) in treated RAW264.7 macrophages were quantified to verify its anti-inflammatory effects. Western blotting was used to investigate the effect of the most potent extract (LP) on TLR-4 related inflammatory proteins (p65, p38, ERK, JNK, IRF3) in RAW264.7 macrophages. All four extracts produced a significant, concentration-dependent reduction in LPS-stimulated nitric oxide, LPS-induced TLR-4 activation in HEK-Blue(TM)-hTLR4 cells and LPS-stimulated cytokines production in RAW264.7 macrophages. The most potent extract, LP, also inhibited all LPS-induced TLR-4 inflammatory proteins. These results provide a basis for understanding the mechanisms underlying the previously demonstrated anti-inflammatory activity of C. nutans extracts.