Abdul Binmahfuth's Personal Blog

 Different people play chess in different styles, no one knows the best way yet. This guide is perhaps useful to computers more than humans, although feel free to take a piece of life-long advice from this article on human behaviour. Source:  https://ar.casact.org/actuaries-versus-artificial-intelligence-what-do-actuaries-do-what-will-they-do/ The participants of this study are merely two chess programs I wrote. With the best of my abilities, I tried to give them some sort of personality that is reflected in their style of play. To understand how to create a "personality" in a program, it is helpful to understand the most common algorithms used in chess. Broadly speaking, designing a chess engine involves two parts: The Risk Assessment part and The Search part. For the latter, there is a pretty standard and efficient algorithm that searches for the best piece to move called the minimax. Thus I won't be altering the search algorithm much. I will, however, alter the risk as

https://www.gocoffeego.com/dbimages/148/roasting@2x.jpg Coffee roasting is widely considered to be an art form among roasters that requires immense dedication to the craftsmanship. It certainly looks like an art considering how many people can't function normally without their morning cup of coffee. Coffee roasting is arguably the key transformable step in the coffee cycle, which usually starts by harvesting coffee cherries, then drying these cherries in numerous different methods, and usually ends up in the morning mugs of office workers (figure 1). Before coffee roasting, the coffee beans hardly resemble our beloved morning coffee in taste, look or smell. As artistic as it sounds, coffee roasting can be quantified to a large degree and can be turned to a scientific and engineering discipline. The motivation behind this article is to explore the usage of mathematical modelling and artificial intelligence to aid commercial coffee roasters to achieve a high level of consistenc

Can we blame bats for transmitting COVID-19 to humans? starting one of the most horrific pandemics and economic crises in the history of mankind. Does batman deserve to feel awkward when bowing to NHS staff? Source:  www.shutupandtakemymoney.com/what-a-bad-time-to-dress-up-as-a-bat-batman-meme/ It is known that bats can harbour different strains of viruses without being infected due to their amazing immune system that limits inflammation [1]. Nevertheless, that is not a valid proof to put the blame on bats straight away, it just puts bats as a pretty good candidate. In this article, I will take a hands-on approach to investigate the root organism that transmitted COVID-19 to humans by taking the bioinformatics rout. I will analyse a sequence taken from a faecal swap of common bats in China to try to arrive at a meaningful conclusion; in a way, reconfirming the results of this peer-reviewed paper [2]. I will start first by showing the computed results and explain its implications, then

The first article in this series was an introduction to Turing pattern formation, it briefly covered the theory behind the formula, where it is generally applied and experimental proof confirming the theory. In the second article, I explained briefly the concept of genetic circuits; comparing genetics to electronic circuits, and a brief expla natio n of the mechanism of a simple genetic toggle switch circuit. Here, I am going to bring these two branches of science together to try to explain how to construct a genetic circuit that produces patterns in Turing instability fashion. This is a theoretical exercise, we assume that the biological parts  chosen here behave exactly as we want them to behave, which is not necessarily true all the time. I will not cover biological details behind the choice of promoters and genes, instead, we will have an engineering mentality of picking components from the shelf approach. As we will see later, it works in the real world Design From First Principl

In the first article ( here ), we have explored what Turing patterns means in a biological sense by given examples of how it occurs in nature.  The series of the articles is building up to genetically modifying organisms to forward engineer Turing patterns. But first, a clear understanding of genes and gene regulatory networks must be given. Gene Anatomy At a crude level, in any living organisms –with some rare few exceptions–, The DNA acts as the blueprint for computations performed in the cell. It consists of nucleic acid monomers linked together to form polymer chains . There are four main types of nucleic acids, adenine (A), guanine (G) cytosine (C), and thymine (T) [3]. DNA molecules usually come in double-helix strands of polymer chains, as shown in figure 1. The two polymer chains are linked together via hydrogen bonds in the given structure: an adenine (A) base is always linked to a thymine (T) base, and cytosine base (C) is always linked to a guanine (G) base.