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    Berkeley Drinks Less Soda

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    With her article “Faced With a New Tax, Berkeley Drinks Less Soda,” published in The Upshot of the New York Times on August 25, 2016, health care reporter Margot Sanger enters a fierce debate about the impact of the soda tax on the consumption of sugary drink. Since 2014 when the tax first went into effect in Berkeley, California; attempts to impose the tax have been a matter of public controversy, and this is what motivated Sanger to produce this piece. The story’s “Kairotic moment,” as referred to in Chapter Eight of Writing Arguments (WA), is the new study of the tax in California, which “adds to the evidence” that taxing sugar-sweetened beverages is not the main reason for the reduction of it’s consumption (A3). Throughout the article, the author applies various sources to strengthen the appeals to ethos and logos of her argument. However, her writing style and choice of original genre weakens her appeals to pathos and ultimately, the overall effectiveness of her argument. In addition, Sanger’s inconsistency in her message also reduces her credibility, despite her success in establishing the argument’s ethos appeals early in the article. Sanger uses short sentences with simple and concrete words in her writing, which makes her message easy to understand and suitable for a wide range of audience. She is also careful with her word choices by replacing “soda” with its synonyms such as sugary drink, sweetened beverages, etc. to avoid repetitions. Unfortunately, despite her…

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    Seth is the Goddess of Storms/Chaos/Evil. He was known for his animal head, often described as Hippopotamus, pig , or a Donkey. Seth was know as many different names such as Set, Setekh, Sutekh and Suty. Geb and Nut were the parents of Seth. Seth was the brother of Isis, Osiris and Nepthys. Nepthys was not just his sister they were married as well. Seth was jealous of Osiris because he was king. One day he attacked Osiris and chopped him up into 14 pieces and distributed them throughout…

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    After that is done, then one will want to start loosening the lug nuts. Do not take them all the way off, just loosen them a little. This will make it easier for one to take the tire off later. However, if someone does not loosen the lug nuts, then when their car and tire is lifted up, it will spin in the air. Lug nuts are tight on the wheel and when one tries to take them off, then they will want to be able to use the ground in their favor. The ground will work as a clamp, holding the wheel in…

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    Rover Experiment

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    variable, or what the scientist changes in an experiment. Then, turn the rover six times towards yourself, and keep count by using the sticky dot. Always turn the rover six times because this is a constant and should not be changed. Next, place the rover on the floor and let it roll. Make sure to use the same surface every time as a constant variable. Follow it and write down the farthest point it travels (or where it stops). The distance traveled -or dependant variable- should be recorded in…

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    networks are designed with the same number of nodes NA=NB=N. Then, we coupled the two isolated networks with a certain preferences. Watts and Strogatz in their seminal paper discovered that many real-world networks are neither random nor regular but somewhere in between, and they proposed a method for constructing such networks, i.e., WS networks[5]. Given that, we created the small-world modular networks model as follows. First, M isolated modules, each with the WS structure, are constructed,…

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    Ramp Physics Lab Report

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    Answers: 1. Segment A (Position-Time on Ramp): The graph is a curve. On any graph that curves, the slope or steepness of the graph changes from one point on the graph to another. Since the slope is constantly changing, the velocity is non-constant. Also, as the graph lies above the x-axis and its slope is increasing, the velocity of the object is also increasing (speeding up) in a positive left direction. Segment B (Position-Time on Flat Surface): The graph is a straight line, which represents…

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    Essay On Group Reflection

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    There were 12 members in my LAPD group presentation including myself. It was my first time having to work with people that I have just met to produce a 50-minute presentation. Before forming a group, I was worried as we are to work in big groups and group size is one of the main factors that may affect a group performance. At first, I felt like we could not delegate our roles equally, as I had past experiences of doing most of the group work. However, during the first workshop, our tutor gave…

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    The second source is a book which introduced the basic concepts and applications of this methodology. The authors concentrated on the causal discovery of networks and the techniques of using Bayesian networks. Furthermore, they discussed the utilisation of this methodology for causal modelling. This source is important at the initial stage of the project as it contributes to the decision-making process at the modelling technique selection stage. However, it is not as important as the other two…

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    Best-First Search Paper

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    Beam search is an informed algorithm for searching a graph that extends the Breadth-First search (Jungwirth, 2006). The Breadth-First search is essentially a special-case Best-First search where the evaluation function, f(n) is the same as the heuristics function, h(n) (JONES, 2008). Therefore in order to properly discuss Beam search, there is the need for a brief introduction to Best-First algorithm. The Best-First search traverses a tree from top to bottom and searches for nodes on the same…

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    Strength All the data obtained from this experiment is plotted on the graph. The accuracy and precision can be determined from the graph. Based on the graph , as the line do not pass the origin , it can be deducted that the result is fairly accurate. Since there are few outliers on the graph , the precision of this graph is moderate. Accuracy of the graph is affected by systematic errors while the precision is affected by random errors. A few measures had been taken prior in getting more…

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