放开我╭(╯^╰)╮我要水！

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Features of academic writing

In order to understand what we mean by features of writing style for studying law at university, we need to examine the difference between writing for aca- demic and professional purposes and other forms of writing. Thus, before you start writing, your  rst step is to develop your ability and skills in using different degrees of formality in English.

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Informal and semi-formal English

In everyday communication – both oral and written – we generally use informal and semi-formal English, as shown in the following examples. Read these sen- tences carefully and note how English is used:

• Police in the dock over evidence to foreign courts.
• You reckon to finish the essay by next Friday?
• You mustn’t drive through a red light, it’s an offence.
• He’s been pinching money from the till for donkey’s years, but when his boss caught him he knew he was in hot water.
• The Chairman stepped down as boss of BP with a bitter sideswipe at critics.
• We can’t make head or tail of this report.
• If you can identify any of the yobs call Crimestoppers anonymously on 0110222333.
• A tax dodger buried ￡140,000 in his aunt’s grave in a bid to fool the Inland Revenue.
• I wouldn’t believe a word he says, he’s a conman.
• She thought she could get away with it but she was nicked for shoplifting.
  

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Use of vocabulary

The following table refers to the above examples and provides the informal and semi-formal words and phrases and their standard English equivalent.

Sentence number	Informal/semi-formal usage	Type	Meaning/standard Enligsh usage
1	in the dock	(colloquial)	on trial
2	reckon	(colloquial)	expect
3	musn't	(colloquial)	must not
4	pinch	(colloquial)	steal
	for donkey's years	(colloquial)	for a long time
	in hot water	(colloquial)	in trouble
5	step down	(phrasal verb)	resign
6	can't make head or tail of this report	(idiom)	cannot understand it at all
7	yobs	(slang)	rude, noisy, aggressive youths
8	doger	(slang)	elusive; a person who evaades paying taxes by trickery
	in a bid to	(colloquial)	in an attempt to
9	conman	(slang)	swindler
10	get away with it	(phrasal verb)	do it without being caught/ punished
	nicked	(slang)	arrested

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兄弟不简单呐

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zyit 发表于 2017-3-31 20:25
兄弟不简单呐

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于是我又有动力水了

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1. \documentclass{book}
   
2. \usepackage{graphicx}
   
3. \usepackage{enumitem}
   
4. \usepackage{changepage}
   
5. \usepackage{multicol}
   
6. \usepackage{chemfig}
   
7. \usepackage{scrextend}
   
8. \setlength\parindent{0pt}
   
9. \setlength\parskip{4pt}
   
10. \setdescription{labelsep=\textwidth, format = \normalfont \textit}
    
11. \usepackage[textfont=it,labelfont=bf]{caption}
    
12. \graphicspath{{./figure/}}
    
13. 
    
14. \newenvironment{pquote}{\begin{adjustwidth}{1em}{1em}
    
15. \begin{quote} \small}
    
16. {\end{quote}\end{adjustwidth}}

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1. \begin{document}
   
2. \chapter{Preface}
   
3. 
   
4. \section{The Strange History of This Book}
   
5. 
   
6. In January 1999 I was preparing to teach an introductory programming class in Java.
   
7. I had taught it three times and I was getting frustrated. The failure rate in the class
   
8. was too high and, even for students who succeeded, the overall level of achievement was
   
9. too low.
   
10. 
    
11. One of the problems I saw was the books. They were too big, with too much unnecessary
    
12. detail about Java, and not enough high-level guidance about how to program. And they
    
13. all suffered from the trap door effect: they would start out easy, proceed gradually, and
    
14. then somewhere around Chapter 5 the bottom would fall out. The students would get
    
15. too much new material, too fast, and I would spend the rest of the semester picking up
    
16. the pieces.
    
17. 
    
18. Two weeks before the first day of classes, i decided to write my own book. My goals
    
19. were:
    
20. 
    
21. \begin{itemize}
    
22.         \item Keep it short. It is better for students to read 10 pages than not read 50 pages.
    
23.         \item Be careful with vocabulary. I tried to minimize the jargon and define each term at
    
24.         first use.
    
25.         \item Build gradually. To avoid trap doors, I took the most difficult topics and split them
    
26.         into a series of small steps.
    
27.         \item Focus on programming, not the programming language. I included the minimum
    
28.         useful subset of Java and left out the rest.
    
29. \end{itemize}

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1. I needed a title, so on a whim I chose \textit{How to Think Like a Computer Scientist.}
   
2. 
   
3. My first version was rough, but it worked. Students did the reading, and they understood
   
4. enough that I could spend class time on the hard topics, the interesting topics and (most
   
5. important) letting the students practice.
   
6. 
   
7. I released the book under the GNU Free Documentation License, which allows users
   
8. to copy, modify, and distribute the book.
   
9. 
   
10. What happened next is the cool part. Jeff Elkner, a high school teacher in Virginia,
    
11. adopted my book and translated it into Python. He's sent me a copy of his translation,
    
12. and I had the unusual experience of learning Python by reading my own book. As Green
    
13. Tea Press, I published the first Python version in 2001.
    
14. 
    
15. In 2003 I started teaching at Olin College and I got to teach Python for the first time.
    
16. The contrast with Java was striking. Students struggled less, learned more, worked on
    
17. more interesting projects, and generally had a lot more fun.
    
18. 
    
19. Over the last nine years I continued to develop the book, correcting errors, improving
    
20. some of the examples and adding material, especially exercises.
    
21. 
    
22. The result is this book, now with the less grandiose title \textit{Think Python}. Some of the
    
23. changes are:
    
24. 
    
25. \begin{itemize}
    
26.   \item I added a section about debugging at the end of each chapter.These sections present
    
27.   general techniques for finding and avoiding bugs, and warnings about Python
    
28.   pitfalls.
    
29.   \item I added more exercises, ranging from short tests of understanding to a few substantial
    
30.   projects. And I wrote solutions for most of them.
    
31.   \item I added a series of case studies---longer examples with exercises, solutions, and
    
32.   discussion. Some are based on Swampy, a suit of Python programs I wrote for use
    
33.   in my classes. Swampy, code examples, and some solutions are available from \textit{http://
    
34.   think python.com}.
    
35.   \item I expanded the discussion of program development plans and basic design patterns.
    
36.   \item I added appendices about debugging, analysis of algorithms, and UML diagrams
    
37.   with Lumpy.
    
38. \end{itemize}
    
39. 
    
40. I hope you enjoy working with this book, and that you learn to program and
    
41. think, at least a little bit, like a computer scientist.
    
42. 
    
43. ---Allen B. Downey
    
44. 
    
45. Needham, MA

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1. \chapter{The Way of the Program}
   
2. 
   
3. The goal of this book is to teach you to think like a computer scientist. This way of
   
4. thinking combines some of the best features of mathematics, engineering, and natural
   
5. science. Like mathematicians, computer scientists use formal languages to denote ideas
   
6. (specially computations). Like engineers, they design things, assembling components
   
7. into systems and evolution tradeoffs among alternatives. Like scientists, they observe
   
8. the behavior of complex systems, form hypotheses, and test predictions.
   
9. 
   
10. The single most important skill for a computer scientist is \textbf{problem solving}. Problem
    
11. solving means the ability to formulate programs, think creatively about solutions, and
    
12. express a solution clearly and accurately. As it turns out, the process of learning to
    
13. program is an excellent opportunity to practice problem-solving skills. That's why this
    
14. chapter is called, ``The way of the program.''
    
15. 
    
16. On one level, you will be learning to program, a useful skill by itself. On another level,
    
17. you will use programming as a means to an end. As we go along, that end will become
    
18. clearer.

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1. \section{The Python Programming Language}
   
2. 
   
3. The programming language you will learn is Python. Python is an example of a \textbf{high-
   
4. level language}; other high-level languages you might heard of are C, C$++$, Perl,
   
5. and Java.
   
6. 
   
7. There are also \textbf{low-level languages}. sometimes referred to as ``machine languages'' or
   
8. ``assembly languages.'' Loosely speaking, computers can only run programs written in
   
9. low-level languages. So programs written in a high-level language have to be processed
   
10. before they can run. This extra processing takes some time, which is a small disadvantage
    
11. of high-level languages.
    
12. 
    
13. The advantages are enormous. First, it is much easier to program in a high-level language.
    
14. Programs written in a high-level language take less time to write, they are shorter
    
15. and easier to read, and they are more likely to be correct. Second, high-level languages
    
16. are \textbf{portable}, meaning that they can run on different kinds of computers with few or no
    
17. modifications. Low-level programs can run on only one kind of computer and have to
    
18. be rewritten to run on another.
    
19. 
    
20. Due to these advantages, almost all programs are written in high-level languages. Low-level
    
21. languages are used only for a few specialized applications.
    
22. 
    
23. Two kinds of programs process high-level languages into low-level languages:
    
24. \textbf{interpreters} and \textbf{compilers}. An interpreter reads a high-level language program and executes it,
    
25. meaning that it does what the program says. It processes the program a little at a time,
    
26. alternately reading lines and performing computations. Figure \ref{interpreter}
    
27. shows the structure
    
28. of an interpreter.
    
29. 
    
30. \begin{figure}
    
31. \begin{center}
    
32. \includegraphics[width=2in]{thinkpython001.png}
    
33. \caption{An interpreter process the program a little at a time, alternately reading lines
    
34. and performing computations.}
    
35. \label{interprater}
    
36. \end{center}
    
37. \end{figure}

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1. A compiler reads the program and translates it completely before the program starts
   
2. running. In this context, the high-level language program is called the \textbf{source code}, and the
   
3. translated program is called the \textbf{object code} or the \textbf{executable}. Once a program is
   
4. compiled, you can execute it repeatedly without further translation. Figure \ref{compilers}
   
5. shows the
   
6. structure of a compiler.
   
7. 
   
8. \begin{figure}
   
9. \begin{center}
   
10. \includegraphics[width=2in]{thinkpython002}
    
11. \caption{A compiler translates source code into object code, which is run by a hardware
    
12. executor.}
    
13. \label{compilers}
    
14. \end{center}
    
15. \end{figure}

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1. Python is considered an interpreted language because Python programs are executed
   
2. by an interpreter. There are two ways to use the interpreter: \textbf{interactive mode} and \textbf{script
   
3. mode}. In interactive mode, you type Python programs and the interpreter displays the
   
4. result:
   
5. 
   
6. \begin{pquote}
   
7. \begin{verbatim}
   
8. >>> 1+1
   
9. 2
   
10. \end{verbatim}
    
11. \end{pquote}
    
12. 
    
13. The chevron, \texttt{>>>}, is the \textbf{prompt} the interpreter uses to indicate that it is ready. If you
    
14. type \texttt{1 + 1}, the interpreter replies \texttt{2}.
    
15. 
    
16. Alternatively, you can store code in a file and use the interpreter to execute the contents
    
17. of the file, which is called a \textbf{script}. By convention, Python scripts have names that end
    
18. with \texttt{.py}.
    
19. 
    
20. To execute the script, you have to tell the interpreter the name of the file. If you have a
    
21. script named \texttt{dinsdale.py} and you are working in a UNIX command window, you type
    
22. \texttt{python dinsdale.py}. In other development environments, the details of executing
    
23. scrips are different. You can find instructions for your environment at the Python website
    
24. \textit{http://python.org}.
    
25. 
    
26. Working in interactive mode is convenient for testing small pieces of code because you
    
27. can type and execute them immediately. But for anything more than a few lines, you
    
28. should save your code as a script so you can modify and execute it in the future.

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1. \section{What is a Program?}
   
2. 
   
3. A \textbf{program} is a sequence of instructions that specifies how to perform a computation.
   
4. The computation might be something mathematical, such as solving a system of equations
   
5. or finding the roots of a polynomial, but it can also be a symbolic computations,
   
6. such as searching and replacing text in a document or (strangely enough) compiling a
   
7. program.
   
8. 
   
9. The details look different in different languages, but a few basic instructions appear in
   
10. just about every language:
    
11. 
    
12. \begin{description}
    
13. 
    
14. \item [input:]Get data from the keyboard, a file, or some other device.
    
15. \item [output:] Display data on the screen or send data to a file or other device.
    
16. \item [math:] Perform basic mathematical operations like addition and multiplication.
    
17. \item [conditional execution:] Check for certain conditions and execute the appropriate code.
    
18. \item [repetition:] Perform some action repeatedly, usually with some variation.
    
19. 
    
20. \end{description}
    
21. 
    
22. Believe it or not, that's pretty much all there is to it. Every program you've ever used, no
    
23. matter how complicated, is made up of instructions that look pretty much like these. So
    
24. you can think of programming as the process of breaking a large, complex task into
    
25. smaller and smaller subtasks until the subtasks are simple enough to be performed with
    
26. one of these basic instructions.
    
27. 
    
28. That may be a little vague, but we will come back to this topic when we talk about
    
29. \textbf{algorithms}.

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1. \section{What Is Debugging?}
   
2. 
   
3. Programming is error-prone. For whimsical reasons, programming errors are called
   
4. \textbf{bugs} and the process of tracking them down is called \textbf{debugging}.
   
5. 
   
6. Three kinds of errors can occur in a program: syntax errors, runtime errors, and
   
7. semantic errors. It is useful to distinguish between them in order to track them down more
   
8. quickly.

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