Catalytic cracking of polystyrene pyrolysis oil: Effect of NbO and NiO/NbO catalyst on the liquid product composition.

The catalytic cracking of polystyrene pyrolysis oil was investigated over a NbO and a NiO/NbO catalyst in a fixed bed reactor. First, the pyrolysis of two different polystyrene feedstock (polystyrene foam and polystyrene pellet) was carried out in a semi-batch reactor, and the resulting polystyrene pellets pyrolysis oil was selected for catalytic cracking reaction because of its high liquid yield (85%). Catalytic cracking experiments were then performed at different temperatures (350-500 °C) using NbO or NiO/NbO catalyst.

CT of amebic liver abscess: different morphological types with different clinical features.

Purpose: To identify different morphological types of amebic liver abscess (ALA) based on CT findings and to assess whether they have different clinical features.

Method: CT images of 112 symptomatic patients with ALA were analyzed to identify the imaging features distinctive of each morphological type. The following CT findings were investigated: the presence of abscess wall, rim enhancement, edge characteristic, septa, intermediate density zone, and peripheral hypodensity.

Physical Analysis of Heat for Formation and Entropy of Ceria Oxide Using Topological Indices.

Background: Cerium oxide nanoparticles (CO NPs) have gained their importance as engineered nanomaterials (ENMs) that have wide applications as catalysts in industry, which direct to their prominent occurrence in natural and engineered water systems. Cerium oxide nanoparticles (CO NPs) have gained their importance as engineered nanomaterials (ENMs) that have wide applications as catalysts in industry, which direct to their prominent occurrence in natural and engineered water systems. In wastewater treatment plants, CO NPs can stay colloidally stable and be unconstrained in the secondary effluents.

Time-dependent AI-Modeling of the anticancer efficacy of synthesized gallic acid analogues.

Background/aim: Main objective of this study is mapping of the anticancer efficacy of synthesized gallic acid analogues using modeling and artificial intelligence (AI) over a large range of concentrations and exposure times to explore the underline mechanisms of drug action and draw careful inferences regarding drug response heterogeneity.

Methods: Two series of gallic acid derivatives i.e.

Cancer drug therapy and stochastic modeling of "nano-motors".

Background: Controlled inhibition of kinesin motor proteins is highly desired in the field of oncology. Among other interventions, there exists "targeted chemotherapeutic regime/options" of selective Eg5 competitive and allosteric inhibitors, inducing cancer cell apoptosis and tumor regression with improved safety profiles.

Research Question: Though promising, such studies are still under clinical trials, for the discovery of efficient and least harmful Eg5 inhibitors.