Plasmonic Superparamagnetic SPION@Ag@chitosan Core-shell: Uptake and Nitric Oxide Inhibition by Colorectal Cell Lines

Using Fusarium oxysporum species (F. oxysporum), a green synthesis of super-paramagnet iron oxide @silver@ Chitosan (SPION@Ag@Cs) was achieved. The physico-chemical characteristics of the SPION@Ag@Cs nanocomposite revealed the development of superparamagnetic phases of iron oxide (Fe₂O₃), as well as fluorescence, Raman absorption, and biocompatibility. Drug and gene delivery, and diagnosis, are all possibilities for the nanocomposite. The uptake of nitric oxide by HT-29 colorectal cell lines is examined in this article, for up to 72 h, the cytotoxicity of the HCT116 cell line was investigated. These characteristics were compared to Streptomyces griseus fungal species (S. griseus) which develops Fe₃O₄ under the same preparation conditions.

     

Optimal Bottleneck-Driven Deep Belief Network Enabled Malware Classification on IoT-Cloud Environment

Cloud Computing (CC) is the most promising and advanced technology to store data and offer online services in an effective manner. When such fast evolving technologies are used in the protection of computer-based systems from cyberattacks, it brings several advantages compared to conventional data protection methods. Some of the computer-based systems that effectively protect the data include Cyber-Physical Systems (CPS), Internet of Things (IoT), mobile devices, desktop and laptop computer, and critical systems. Malicious software (malware) is nothing but a type of software that targets the computer-based systems so as to launch cyber-attacks and threaten the integrity, secrecy, and accessibility of the information. The current study focuses on design of Optimal Bottleneck driven Deep Belief Network-enabled Cybersecurity Malware Classification (OBDDBN-CMC) model. The presented OBDDBN-CMC model intends to recognize and classify the malware that exists in IoT-based cloud platform. To attain this, Z-score data normalization is utilized to scale the data into a uniform format. In addition, BDDBN model is also exploited for recognition and categorization of malware. To effectually fine-tune the hyperparameters related to BDDBN model, Grasshopper Optimization Algorithm (GOA) is applied. This scenario enhances the classification results and also shows the novelty of current study. The experimental analysis was conducted upon OBDDBN-CMC model for validation and the results confirmed the enhanced performance of OBDDBN-CMC model over recent approaches.     

Activated nitriles in heterocyclic synthesis: A Novel Synthesis of Pyrimidine Derivatives

The reaction of 3-amino-2,4-diethoxycarbonylcrotononitrile with cinnamonitrile derivatives afforded the pyrimidines 5a--d and not the pyridines 4 as expected from literature. Similarly pyrimidines 5e--h were produced when 3-amino-2,4-dicyanocrotononitrile was treated with the same reagent. The structure was established based on MS and high resolution ¹H-n.m.r. spectroscopy.     

Simulation and Optimization of Back Surface Field for Efficient HIT Solar Cells

Silicon - We investigate an appropriate material for the optimisation of Back Surface Field (BSF) layer in Heterojunction with Intrinsic thin layer (HIT) solar cells:...     

Insight on the Dependence of the Drug Delivery Applications of Mesoporous Silica Nanoparticles on Their Physical Properties

Silicon - Mesoporous silica nanoparticles (MSNs) are fascinating due to their interesting properties and applications. The optimization of MSNs for drug delivery applications was achieved by...