Cancer is considered one of the primary diseases that cause morbidity and mortality in millions of people worldwide and due to its prevalence, there is undoubtedly an unmet need to discover novel anticancer drugs. However, the traditional process of drug discovery and development is lengthy and expensive, so the application of in silico techniques and optimization algorithms in drug discovery projects can provide a solution, saving time and costs. A set of 617 approved anticancer drugs, constituting the active domain, and a set of 2,892 natural products, constituting the inactive domain, were employed to build predictive models and to index natural products for their anticancer bioactivity. Using the iterative stochastic elimination optimization technique, we obtained a highly discriminative and robust model, with an area under the curve of 0.95. Twelve natural products that scored highly as potential anticancer drug candidates are disclosed. Searching the scientific literature revealed that few of those molecules (Neoechinulin, Colchicine, and Piperolactam) have already been experimentally screened for their anticancer activity and found active. The other phytochemicals await evaluation for their anticancerous activity in wet lab.

The proposed anti-inflammatory model can be utilized for the virtual screening of large chemical databases and for indexing natural products for potential anti-inflammatory activity.

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New generations are using and playing with mobile and computer applications extensively. These applications are the outcomes of programming work that involves skills, such as computational and algorithmic thinking. Learning programming is not easy for students children. In recent years, academic institutions like the Massachusetts Institute of Technology (MIT) and hi-tech companies, such as Google and Khan Academy, have introduced online environments to facilitate the teaching and learning of programming. Most of these programming environments are web-based, and interactive and are supported with visual multimedia features. Therefore, they have become easy to use, very attractive and helpful for teaching children how to program and to develop their algorithmic and computational thinking skills. The proposed presentation will describe research that examined the teaching of a course to primary school children based on three on-line interactive environments: "Plastelina" for logic games, "Code with Anna and Elsa" via the Hour of Code project block-oriented programming environment, for block programming and "Turtle Academy" for textual programming in the Logo language. The current research included the development, implementation and evaluation of the course at an elementary school. In addition, it was aimed at investigating the pupils' attitudes toward the learning of computer programming, both before and after participation in the course. The results revealed that the pupils' attitudes towards programming remained positive also also after the participation in the course. It was also found that programming improved children's problemsolving skills.

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