时间:2018-12-28 作者:英语课 分类:英语语言学习


英语课
Robyn Williams: I wear sandals to work. So Does Jonathan Green. We do so for two reasons. First, to make at least one thing Gerard Henderson writes – just one – to be true. He’s always calling us at the A.B.C. Sandalistas – an odd, rather ugly term implying Maoist tendencies with basket-weaving undertones. So we eschew 1 our designer brogues and wear brown New Zealand made Roman Sandals to work instead.
But the other reason we do so is to emulate 2 Einstein, especially in this 101st anniversary of General Relativity. Why? Well here’s physicist 3 Len Fisher to reveal all.
Len Fisher: I’d like to talk to you today about Einstein’s socks – well, not so much about his socks, but about the way of thinking that led him to decide never to wear them, and which also led him to his theories of relativity.
Einstein was very proud of the fact that he never wore socks. On one visit to the University of Oxford 4, he wrote to his cousin and eventual 5 second wife Elsa, “Even on the most solemn occasions I got away without wearing socks and hid the lack of civilization in high boots.” But he wasn’t just doing this out of rebellion. He explained his reasons in a letter to his friend Philippe Halsmann, whose iconic photograph of Einstein would eventually appear on a U.S. stamp. “When I was young,” he said “I found out that the big toe always ends up making a hole in a sock. So I stopped wearing socks.”
The clue to Einstein’s thinking here lies in that little word “so”, but there’s a logical leap. OK, when we look at photographs of Einstein in sandals, we can see that his big toe projects well beyond the second. But why should this mean that he had to give up the comfort of socks? Why not just buy new ones when the old ones wore out?
What surely swung Einstein’s decision was the underlying 6 thought “what if?” “What if I gave up wearing socks?” is not a question that would occur to many of us, but to Einstein it was a natural question to ask, and one that led to a basically barefoot existence.
When he was 15 or 16 he asked another “what if?” question in a letter to his uncle, Cäsar Koch - what would a light beam look like if you could run alongside it at the same speed?
Probably he didn’t realize it at the time, but he was asking a very fundamental question that was already bugging 7 physicists 8. The problem was this. If you could keep pace with a light beam (known by this time to be an oscillating wave travelling through space), then it would appear to your eyes to be stationary 9, just as a wave travelling across water would appear to have a constant, immobile shape if you could run alongside it. Yet physicists knew that Maxwell’s equations, which describe the propagation of light waves, forbid the occurrence of such a stationary state.
Ten years after he first raised the question, Einstein came up with an answer in the form of another “what if?” question. What if you couldn’t ever run alongside a light wave? What if, no matter how fast you ran, the light wave always caught up with you and passed you at the same speed as if you weren’t running at all? Then it would simply be zipping past, no matter how fast you were travelling, and would never appear stationary. In exploring this possibility, which sounds as though it comes from a world of cartoon fantasy, Einstein came up with his Special Theory of Relativity.
In fact, the world of cartoon fantasy is littered with “what if” scenarios 11. They’ve even been encapsulated as the laws of cartoon physics, such as the law that characters are never affected 12 by the law of gravity until they notice it – after they’ve stepped off the edge of a cliff, for example, and remained suspended until they have suddenly realized their perilous 13 situation and gone plummeting 14 to the round.
The world of cartoon fantasy doesn’t concur 15 with our observations of reality, but many of the major advances in science have come through checking out the answers to “what if” questions. One of the best known was due to Isaac Newton, who wondered what would happen if all bodies, no matter how far apart, exerted an attractive force on each other that diminished with the square of the distance between them.
Newton checked out his speculation 16 by calculating what the orbits of the Moon and planets might be if such an attractive force did exist, and of course he got answers that conformed with reality and supported his idea about the force that we now know as gravity. More recently, a world-wide team of scientists has confirmed the existence of waves in the gravitational field – a prediction that was made by Einstein when he asked “what if” gravity was a geometric property of space and time.
But “what if” questions are going a lot further these days, and impinging on our lives in ways that more people should know about.
Probably the simplest to grasp conceptually is the idea of scenario 10 planning. In developing policies for flood or fire protection, for example, a responsible body might ask “what if” so may houses are built in an area, or “what if” rainfalls reach a particular level that might produce flooding. Similarly when it comes to protection against terrorist attacks a series of “what if” questions is likely to be high on the agenda. In all cases, a set of possible scenarios is drawn 17 up, the likelihood of their occurrence analyzed 18, and appropriate measures put in place. Or so the theory goes.
One of the great problems with this sort of approach is the common assumption that the future is likely to be the same as the past. When the first attempts at systematic 19 weather forecasting were made, one idea was to look back through the records for a day where the weather was much the same as the day when the forecast was being made. The assumption was that the weather on the following day would be the same as the weather on the following day in the historical past.
But surprising events are always occurring to disrupt this sort of forecasting. When IBM built its first computers in the early 1940s, President Thomas Watson famously predicted a world market of “maybe five computers.” When it comes to weather forecasting, longer-range forecasts are being blown apart by the accelerating pace of global warming. In my own world of nanotechnology, the discovery of graphene has revolutionized the electronic applications in particular.
What we need, and what is happening, is a different sort of “what if” question – one that is relevant to today’s needs and the pace of change. It is coming in the form of computer modeling of our complex world, where the “what if” question comes in the form “what if this particular model represents reality?” with the answer “well in that case this is how the system will evolve and change over time.”
Some of the greatest investment in this area has come in the form of climate modeling, which has been the subject of other programmes in this series. But the biggest insights, the ones that policy-makers really need to sit up and take notice of, have barely reached the fringes of public consciousness.
The first, and most important, is that all complex systems have a built-in capacity to change suddenly to a different state. By complex systems I mean systems of many interacting parts, where the emergent properties of the whole can be much greater than the sum of its parts. So banking 20 systems may collapse 21 almost without warning; societies may burst into rebellion; the composition of the bacterial 22 ecosystem 23 in your gut 24 or the wider ecosystem of which you are a part may suddenly change.
No amount of forward planning can prevent such changes in the long term. Such planning is too often based on the political assumption that some particular set of dogmas ought to work, therefore it must be possible to make them work. But instead of aiming to set our complex socio-economic-ecological world in concrete in this way, we should instead be aiming for resilience – the ability either to bounce back from sudden change or to accept and adapt to it, if that seems the better option. This is where the frequently-bandied idea of big data comes into the frame, usually with the idea that, if we only know enough about the system, we will be able to control how it behaves.
Fat chance. One of the strongest insights from our era of big data and computer modeling is that tiny changes in one part of the system can give rise to dramatic change in other parts.
So our modern “what if?” question becomes “when?” Not what will happen if there is a sudden change in our apparently 25 well-regulated and stable world, but when such a change inevitably 26 happens, will we be prepared?
At the moment we are not, for the simple reason that the pace of change when it happens is too rapid for human institutions to cope with. It is for this reason that stock markets, not to mention institutions like Google, Facebook and Twitter, now rely on algorithms to make decisions for them.
An algorithm is a set of pre-decided rules that take data like stock prices, incomes or our personal habits and use them to develop actions and policies, from choosing which advertisements to target us with to where to put the money that we have saved for our retirement 27. Governments are now using algorithms as a convenient way to develop social policy, in a powerful and dangerous mix of opacity 28 and executability. Neither we nor the developers can see what is going on beneath the surface when an algorithm is implemented 29, yet we can be deeply affected by the result. To give just one example, military drones are directed by algorithms both to seek out targets and to take whatever their owners conceive to be “appropriate” action against them.
With the advent 30 of algorithmic governance in many areas we have come to an era where “what if?” has been replaced by “what”. An algorithm is told what the data are, and proceeds from there unquestioningly. But what if different variables might produce a different outcome? What if, for example, we could input 31 human values and aspirations 32, rather than incomes, ages and social status, into the algorithms that are coming to control our lives?
Einstein once said: “Why does this magnificent applied 33 science which saves work and makes life easier bring us so little happiness? The simple answer runs: Because we have not yet learned to make sensible use of it.”
My question to you is “What if we could learn to make sensible use of the insights that we are rapidly developing into how our complex world works? What if we could use our models and our tools to promote human happiness, rather than just big profits for big business? What if we could plan for inevitable 34 change, to be met with resilience, rather than try vainly to lock ourselves in to an imaginary utopia that has never existed and never can exist? What if we could discard the stifling 35 socks of reality and walk bare-footed into a freer and brighter future?”
Ah, well – I may not be an Einstein, but at least I can dream.
Robyn Williams: You can, Len. You can. Len Fisher used to be at the CSIRO and now does physics in Bristol. That’s where he polishes his Ig Nobel Prize. Next week, what if we culled 36 those noisy mynahs? And I don’t mean Clive Palmer or Twiggy 37 Forest, I mean those terrifying native birds which now destroy so many little ones. Has their time finally arrived? Sue Taylor in Melbourne comments. I’m Robyn Williams.

1 eschew
v.避开,戒绝
  • Eschew fattening foods if you want to lose weight.你如想减肥,就不要吃致肥的食物。
  • Good kid should eschew bad company.好孩子应避免交坏朋友。
2 emulate
v.努力赶上或超越,与…竞争;效仿
  • You must work hard to emulate your sister.你必须努力工作,赶上你姐姐。
  • You must look at the film and try to emulate his behavior.你们必须观看这部电影,并尽力模仿他的动作。
3 physicist
n.物理学家,研究物理学的人
  • He is a physicist of the first rank.他是一流的物理学家。
  • The successful physicist never puts on airs.这位卓有成就的物理学家从不摆架子。
4 Oxford
n.牛津(英国城市)
  • At present he has become a Professor of Chemistry at Oxford.他现在已是牛津大学的化学教授了。
  • This is where the road to Oxford joins the road to London.这是去牛津的路与去伦敦的路的汇合处。
5 eventual
adj.最后的,结局的,最终的
  • Several schools face eventual closure.几所学校面临最终关闭。
  • Both parties expressed optimism about an eventual solution.双方对问题的最终解决都表示乐观。
6 underlying
adj.在下面的,含蓄的,潜在的
  • The underlying theme of the novel is very serious.小说隐含的主题是十分严肃的。
  • This word has its underlying meaning.这个单词有它潜在的含义。
7 bugging
[法] 窃听
  • Okay, then let's get the show on the road and I'll stop bugging you. 好,那么让我们开始动起来,我将不再惹你生气。 来自辞典例句
  • Go fly a kite and stop bugging me. 走开,别烦我。 来自英汉 - 翻译样例 - 口语
8 physicists
物理学家( physicist的名词复数 )
  • For many particle physicists, however, it was a year of frustration. 对于许多粒子物理学家来说,这是受挫折的一年。 来自英汉非文学 - 科技
  • Physicists seek rules or patterns to provide a framework. 物理学家寻求用法则或图式来构成一个框架。
9 stationary
adj.固定的,静止不动的
  • A stationary object is easy to be aimed at.一个静止不动的物体是容易瞄准的。
  • Wait until the bus is stationary before you get off.你要等公共汽车停稳了再下车。
10 scenario
n.剧本,脚本;概要
  • But the birth scenario is not completely accurate.然而分娩脚本并非完全准确的。
  • This is a totally different scenario.这是完全不同的剧本。
11 scenarios
n.[意]情节;剧本;事态;脚本
  • Further, graphite cores may be safer than non-graphite cores under some accident scenarios. 再者,根据一些事故解说,石墨堆芯可比非石墨堆芯更安全一些。 来自英汉非文学 - 环境法 - 环境法
  • Again, scenarios should make it clear which modes are acceptable to users in various contexts. 同样,我们可以运用场景剧本来搞清楚在不同情境下哪些模式可被用户接受。 来自About Face 3交互设计精髓
12 affected
adj.不自然的,假装的
  • She showed an affected interest in our subject.她假装对我们的课题感到兴趣。
  • His manners are affected.他的态度不自然。
13 perilous
adj.危险的,冒险的
  • The journey through the jungle was perilous.穿过丛林的旅行充满了危险。
  • We have been carried in safety through a perilous crisis.历经一连串危机,我们如今已安然无恙。
14 plummeting
v.垂直落下,骤然跌落( plummet的现在分词 )
  • Prices are rising, falling, going up, going down, shooting up, plummeting, etc. 物价在上涨、下跌、上升、下落、猛然上涨、骤然下跌等。 来自辞典例句
  • The enemy plane went plummeting into the sea. 敌机直直掉进海里。 来自辞典例句
15 concur
v.同意,意见一致,互助,同时发生
  • Wealth and happiness do not always concur.财富与幸福并非总是并存的。
  • I concur with the speaker in condemning what has been done.我同意发言者对所做的事加以谴责。
16 speculation
n.思索,沉思;猜测;投机
  • Her mind is occupied with speculation.她的头脑忙于思考。
  • There is widespread speculation that he is going to resign.人们普遍推测他要辞职。
17 drawn
v.拖,拉,拔出;adj.憔悴的,紧张的
  • All the characters in the story are drawn from life.故事中的所有人物都取材于生活。
  • Her gaze was drawn irresistibly to the scene outside.她的目光禁不住被外面的风景所吸引。
18 analyzed
v.分析( analyze的过去式和过去分词 );分解;解释;对…进行心理分析
  • The doctors analyzed the blood sample for anemia. 医生们分析了贫血的血样。 来自《简明英汉词典》
  • The young man did not analyze the process of his captivation and enrapturement, for love to him was a mystery and could not be analyzed. 这年轻人没有分析自己蛊惑著迷的过程,因为对他来说,爱是个不可分析的迷。 来自《简明英汉词典》
19 systematic
adj.有系统的,有计划的,有方法的
  • The way he works isn't very systematic.他的工作不是很有条理。
  • The teacher made a systematic work of teaching.这个教师进行系统的教学工作。
20 banking
n.银行业,银行学,金融业
  • John is launching his son on a career in banking.约翰打算让儿子在银行界谋一个新职位。
  • He possesses an extensive knowledge of banking.他具有广博的银行业务知识。
21 collapse
vi.累倒;昏倒;倒塌;塌陷
  • The country's economy is on the verge of collapse.国家的经济已到了崩溃的边缘。
  • The engineer made a complete diagnosis of the bridge's collapse.工程师对桥的倒塌做了一次彻底的调查分析。
22 bacterial
a.细菌的
  • Bacterial reproduction is accelerated in weightless space. 在失重的空间,细菌繁殖加快了。
  • Brain lesions can be caused by bacterial infections. 大脑损伤可能由细菌感染引起。
23 ecosystem
n.生态系统
  • This destroyed the ecosystem of the island.这样破坏了岛上的生态系统。
  • We all have an interest in maintaining the integrity of the ecosystem.维持生态系统的完整是我们共同的利益。
24 gut
n.[pl.]胆量;内脏;adj.本能的;vt.取出内脏
  • It is not always necessary to gut the fish prior to freezing.冷冻鱼之前并不总是需要先把内脏掏空。
  • My immediate gut feeling was to refuse.我本能的直接反应是拒绝。
25 apparently
adv.显然地;表面上,似乎
  • An apparently blind alley leads suddenly into an open space.山穷水尽,豁然开朗。
  • He was apparently much surprised at the news.他对那个消息显然感到十分惊异。
26 inevitably
adv.不可避免地;必然发生地
  • In the way you go on,you are inevitably coming apart.照你们这样下去,毫无疑问是会散伙的。
  • Technological changes will inevitably lead to unemployment.技术变革必然会导致失业。
27 retirement
n.退休,退职
  • She wanted to enjoy her retirement without being beset by financial worries.她想享受退休生活而不必为金钱担忧。
  • I have to put everything away for my retirement.我必须把一切都积蓄起来以便退休后用。
28 opacity
n.不透明;难懂
  • He insisted that the mineral content of the water determined the opacity.他坚持认为水的清澈程度取决于其中矿物质的含量。
  • Opacity of the eye lens can be induced by deficiency of certain vitamins.眼球晶状体的混浊可由缺乏某些维生素造成。
29 implemented
v.实现( implement的过去式和过去分词 );执行;贯彻;使生效
  • This agreement, if not implemented, is a mere scrap of paper. 这个协定如不执行只不过是一纸空文。 来自《现代汉英综合大词典》
  • The economy is in danger of collapse unless far-reaching reforms are implemented. 如果不实施影响深远的改革,经济就面临崩溃的危险。 来自辞典例句
30 advent
n.(重要事件等的)到来,来临
  • Swallows come by groups at the advent of spring. 春天来临时燕子成群飞来。
  • The advent of the Euro will redefine Europe.欧元的出现将重新定义欧洲。
31 input
n.输入(物);投入;vt.把(数据等)输入计算机
  • I will forever be grateful for his considerable input.我将永远感激他的大量投入。
  • All this information had to be input onto the computer.所有这些信息都必须输入计算机。
32 aspirations
强烈的愿望( aspiration的名词复数 ); 志向; 发送气音; 发 h 音
  • I didn't realize you had political aspirations. 我没有意识到你有政治上的抱负。
  • The new treaty embodies the aspirations of most nonaligned countries. 新条约体现了大多数不结盟国家的愿望。
33 applied
adj.应用的;v.应用,适用
  • She plans to take a course in applied linguistics.她打算学习应用语言学课程。
  • This cream is best applied to the face at night.这种乳霜最好晚上擦脸用。
34 inevitable
adj.不可避免的,必然发生的
  • Mary was wearing her inevitable large hat.玛丽戴着她总是戴的那顶大帽子。
  • The defeat had inevitable consequences for British policy.战败对英国政策不可避免地产生了影响。
35 stifling
a.令人窒息的
  • The weather is stifling. It looks like rain. 今天太闷热,光景是要下雨。
  • We were stifling in that hot room with all the windows closed. 我们在那间关着窗户的热屋子里,简直透不过气来。
36 culled
v.挑选,剔除( cull的过去式和过去分词 )
  • The herd must be culled. 必须有选择地杀掉部分牧畜。 来自辞典例句
  • The facts were culled from various sources. 这些事实是从各方收集到的。 来自辞典例句
37 twiggy
多细枝的,小枝繁茂的
  • Twiggy was a little of both boy and girl a mirror of her time. 崔姬又像男孩又像女孩,是她当时真实的生活写照。
学英语单词
a harbour of refuge
Adesmia
Akbakay
aluminium-foil with paper lining
AMEDS, AMedS
Anaerorhabdus
angles back to back
anthroposophies
aqua mirabilis
baccha (allobaccha) nubilipennis
back-up copy
ballad of reading gaol
bangle ear
bearing hub
blue(water) gas
book piracy
born-karman theory
brass polish
budget talks
cantaloupe melon
certificate references
coasting surface
completely mixed reactor
computer application for measurement and control
conducting-core heterofilament
critical energy of reaction
dasyuridaes
Dominique
ernst lubitsches
expectoratory
failure diagnostic
failure voltage
farri
fast-fading
fire tile
Fitch,Val
footcandlle
gelatt
genus Javanthropus
go formal
Google operating system
graphemic
haemal zygapophysis
happenin'
hardware select
Holland, Sir Sidney George
identification name
importuning
isotonic nucleus
jordan snow plow
king leopold ra.
laboulbenia ophioneae
line outage
live fish hold
long-stem
low - pressure system
mail person
malawar
marrinson
mcilvain
menifest of clearance
mini-trench
Multi-mask
multigroup Monte Carlo method
multilevel hierarchy
nonsupervised
operating system efficiency
panther lilies
PDLP
phase-locked speed control system
pixel map
polished-joint hanger
post-communists
radioactive emanations
rational fraction approximation
roof pressure
roots of unity
ruby port
scalenest
sceondary breaker
selective frequency control
sensory spots
signed magnitude computer
single path catalytic reaction
spacer flange
spontaneous gangrene
starves
Stellectomy
storm-clouds
sugarplum
surkamp
swinging-out casement window
teachware
tension management
thymegol
tilting-type
tower's liability
trabeculae corporis cavernosi urethrae
Treitz's Trelat's sign
unquality-like
vintage-car
wycch