【托福动态】英国叫停托福考试 报考人数仍在增长

3月24日,有“留学风向标”之称的第20届“中国国际教育巡回展”抵达上海。在教育展现场,记者获悉,在去年叫停托福考试后,英国已出台政策,该国部分学校已不认可托福考试成绩。托福考试主办方ETS的相关负责人则表示,托福考试的报考人数仍在增长,已在中国增加考场、扩增考位、增加场次。

【托福动态】英国叫停托福考试 报考人数仍在增长图1

部分英国学校不认可托福成绩

“英国不认可托福托业考试对中国学生影响不大。”英国诺丁汉大学国际部张雯告诉记者。

2014年2月,英国广播公司(BBC)栏目揭露该国学生签证系统存在严重造假问题,英国内政部随之暂停了由美国教育考试服务中心(ETS)主持的包括托福、托业在内的全部英语考试项目。

2015年2月20日,英国政府发表声明,从2015年4月6日起,将只承认签证类安全英语语言考试(SELT)作为申请进入英国的签证语言考试。SELT包括且仅包括英国签证类雅思考试(IELTS for UKVI)、生活技能类雅思考试(IELTS Life Skills)以及由伦敦三一学院组织的语言考试成绩。英国境内非欧盟留学生要续签英国签证时,需要再去考一个英国认可的考试。

据介绍,所有到英国读预科以及语言类学校的学生必须参加SELT考试,也就是必须要有雅思成绩;而赴英国攻读本科、硕士、博士学位的留学生,则根据所要申请的学校分为两种情况,一种是申请高度可信赖(HTS)大学,学校可以自主决定是否要求SELT成绩;另一种是申请非高度可信赖(HTS)大学,学生必须有SELT成绩,也就是必须参加雅思考试。

【托福动态】英国叫停托福考试 报考人数仍在增长图2

“学生应该看自己申请的学校是否要求雅思成绩,再来决定是否要参加雅思考试,拿诺丁汉大学为例来讲,除预科和语言类专业外,我们还是承认托福考试成绩的。”

还提醒中国考生,目前中国大陆地区可以提供(签证类雅思考试)IELTS for UKVI考试的有12处考点,香港有1处,总计13处考点,其余国内考点均不在英国签证与移民局认可的范围内。

ETS测评技术有限公司项目经理林琳则表示,英国不认可托福成绩对报考人数影响不大,但报考人数仍在增长,托福对考生未来发展会产生很大影响,所以考试安全性也相应很高。

当谈到托福考试“一位难求”的现象时,林琳介绍说,上海2015年有8个托福考试点,根据去年申请人数状况,已经有了相应调整,包括增加考场、扩增考位、增加场次等。她还提到,下半年考试场次较多,10月有5场考试;11月有6场考试;12月有5场考试。

【出品】雅思阅读机经真题解析-Life code-unlocked

小站独家,雅思阅读机经真题解析。一切患有雅思阅读刷题强迫症的烤鸭,请看这里。小站精心整理了一批雅思阅读机经真题。如果你的剑桥雅思阅读已是烂熟于心,那么这一系列的雅思阅读机经真题真的很适合你,搭配上绝对原创的讲解,还有全文的中文翻译,这等阅读大餐,还等什么!

A

On an airport shuttle bus to the Kavli Institute for Theoretical Physics in
Santa Barbara, Calif, Chris Wiggins took a colleague’s advice and opened a
Microsoft Excel spreadsheet. It had nothing to do with the talk on biopolymer
physics he was invited to give. Rather the columns and rows of numbers that
stared back at him referred to the genetic activity of budding yeast.
Specifically, the numbers represented the amount of messenger RNA (mRNA)
expressed by all 6,200 genes of the yeast over the course of its reproductive
cycle. “It was the first time I ever saw anything like this,” Wiggins recalls of
that spring day in 2002. “How to make sense of all these data?”

B

Instead of shirking from this question, the 36-year-old applied mathematician
and physicist at Columbia University embraced it-and now six years later he
thinks he has an answer. By foraying into fields outside his own, Wiggins has
drudged up tools from a branch of artificial intelligence called machine
learning to model the collective protein-making activity of genes from
real-world biological data. Engineers originally designed these tools in the
late 1950s to predict output from input. Wiggins and his colleagues have now
brought machine learning to the natural sciences and tweaked it so that it can
also tell a story—one not only about input and output but also about what
happens inside a model of gene regulation, the black box in between.

C

The impetus for this work began in the late 1990s, when high-throughput
techniques generated more mRNA expression profiles and DNA sequences than ever
before, “opening up a completely different way of thinking about biological
phenomena,” Wiggins says. Key among these techniques were DNA microarrays, chips
that provide a panoramic view of the activity of genes and their expression
levels in any cell type, simultaneously and under myriad conditions. As noisy
and incomplete as the data were, biologists could now query which genes turn on
or off in different cells and determine the collection of proteins that give
rise to a cell’s characteristic features- healthy or diseased.

D

Yet predicting such gene activity requires uncovering the fundamental rules
that govern it. “Over time, these rules have been locked in by cells,” says
theoretical physicist Harmen Bussemaker, now an associate professor of biology
at Columbia. “Evolution has kept the good stuff.” To find these rules,
scientists needed statistics to infer the interaction between genes and the
proteins that regulate them and to then mathematically describe this network’s
underlying structure-the dynamic pattern of gene and protein activity over time.
But physicists who did not work with particles (or planets, for that matter)
viewed statistics as nothing short of an anathema. “If your experiment requires
statistics,” British physicist Ernest Rutherford once said, “you ought to have
done a better experiment.”

E

But in working with microarrays, “the experiment has been done without you,”
Wiggins explains. “And biology doesn’t hand you a model to make sense of the
data.” Even more challenging, the building blocks that make up DNA, RNA and
proteins are assembled in myriad ways; moreover, subtly different rules of
interaction govern their activity, making it difficult, if not impossible, to
reduce their patterns of interaction to fundamental laws. Some genes and
proteins are not even known. “You are trying to find something compelling about
the natural world in a context where you don’t know very much,” says William
Bialek, a biophysicist at Princeton University. “You’re forced to be agnostic.”
Wiggins believes that many machine-learning algorithms perform well under
precisely these conditions. When working with so many unknown variables,
“machine learning lets the data decide what’s worth looking at,” he says.

F

At the Kavli Institute, Wiggins began building a model of a gene regulatory
network in yeast-the set of rules by which genes and regulators collectively
orchestrate how vigorously DNA is transcribed into mRNA. As he worked with
different algorithms, he started to attend discussions on gene regulation led by
Christina Leslie, who ran the computational biology group at Columbia at the
time. Leslie suggested using a specific machine-learning tool called a
classifier. Say the algorithm must discriminate between pictures that have
bicycles in them and pictures that do not. A classifier sifts through labeled
examples and measures everything it can about them, gradually learning the
decision rules that govern the grouping. From these rules, the algorithm
generates a model that can determine whether or not new pictures have bikes in
them. In gene regulatory networks, the learning task becomes the problem of
predicting whether genes increase or decrease their protein-making activity.

G

The algorithm that Wiggins and Leslie began building in the fall of 2002 was
trained on the DNA sequences and mRNA levels of regulators expressed during a
range of conditions in yeast-when the yeast was cold, hot, starved, and so on.
Specifically, this algorithm-MEDUSA (for motif element discrimination using
sequence agglomeration)—scans every possible pairing between a set of DNA
promoter sequences, called motifs, and regulators. Then, much like a child might
match a list of words with their definitions by drawing a line between the two,
MEDUSA finds the pairing that best improves the fit between the model and the
data it tries to emulate. (Wiggins refers to these pairings as edges.) Each time
MEDUSA finds a pairing, it updates the model by adding a new rule to guide its
search for the next pairing. It then determines the strength of each pairing by
how well the rule improves the existing model. The hierarchy of numbers enables
Wiggins and his colleagues to determine which pairings are more important than
others and how they can collectively influence the activity of each of the
yeast’s 6,200 genes. By adding one pairing at a time, MEDUSA can predict which
genes ratchet up their RNA production or clamp that production down, as well as
reveal the collective mechanisms that orchestrate an organism’s transcriptional
logic.

Questions 1-6

The reading passage has seven paragraphs, A-G

Choose the correct heading for paragraphs A-G from the list below.

Write the correct number, i-x, in boxes 1-6 on your answer sheet.

List of Headings

i. The search for the better-fit matching between the model and the gained
figures to foresee the activities of the genes

ii. The definition of MEDUSA

iii. A flashback of a commencement for a far-reaching breakthrough

iv. A drawing of the gene map

v. An algorithm used to construct a specific model to discern the appearance
of something new by the joint effort of Wiggins and another scientist

vi. An introduction of a background tracing back to the availability of
mature techniques for detailed research on genes

vii. A way out to face the challenge confronting the scientist on the
deciding of researchable data

viii. A failure to find out some specific genes controlling the production of
certain proteins

ix. The use of a means from another domain for reference

x. A tough hurdle on the way to find the law governing the activities of the
genes

Example: Paragraph A iii

1 Paragraph B

2 Paragraph C

3 Paragraph D

4 Paragraph E

5 Paragraph F

6 Paragraph G

Questions 7-9

Do the following statements agree with the information given in Reading
Passage 1?

In boxes 7-9 on your answer sheet, write

TRUE if the statement is true

FALSE if the statement is false

NOT GIVEN if the information is not given in the passage

7. Wiggins is the first man to use DNA microarrays for the research on
genes.

8. There is almost no possibility for the effort to decrease the patterns of
interaction between DNA, RNA and proteins.

9. Wiggins holds a very positive attitude on the future of genetic
research.

Questions 10-13

Summary

Complete the following summary of the paragraphs of Reading Passage, using No
More than Three words from the Reading Passage for each answer. Write your
answers in boxes 10-13 on your answer sheet.

Wiggins states that the astoundingly rapid development of techniques
concerning the components of genes aroused the researchers to look at 10 from a
totally new way. 11 is the heart and soul of these techniques and no matter what
the 12 were, at the same time they can offer a whole picture of the genes’
activities as well as 13 in all types of cells. With these techniques scientists
could locate the exact gene which was on or off to manipulate the production of
the proteins.

(转第二页)

当脱欧成为雅思写作话题

  看着脱欧的新闻,coco不禁职业病滴将视线集中在BBC的图表上。做得真是一流啊!数据清洗,逻辑明确,万一成了雅思的小作文图表题,那该多好啊!

  好了,既然我们已经受惠于汇率10%的下降,也不妨再多占脱欧一个便宜,那就是拿它当雅思小作文图表题练练手吧!

  以下请看题:

  The graphs below show the result of referendum for the UK to

  leave the EU in June 2016. You are required to write an essay about

  150 words to report the main features and make relevant

  comparisons.

  The final percentages and quantities of vote on both

  sides

  How Leave won the referendum against Remain in different areas

  of the UK

  当

  —————我是动人分割线————–

  写作tips:以下句子是BBC专题报道原句,大家可灵活应用到这篇小作文中哦。

  1. “Leave won by 52% to 48%.”

  2. “England voted strongly for Brexit, by 53.4% to 46.6%, as

  did Wales, with Leave getting 52.5% of the vote and Remain

  47.5%.”

  3. “Scotland and Northern Ireland both backed staying in the

  EU. Scotland backed Remain by 62% to 38%, while 55.8% in Northern

  Ireland voted Remain and 44.2% Leave.”

【SAT阅读】阅读选择题常见问题类型

SAT阅读选择题的答案选项一共有5个,对于已经习惯了答案选项是3个和4个的内地考生来说,还是需要一些适应的时间的,通常涉及的问题类型包括:

【SAT阅读】阅读选择题常见问题类型图1

本篇文章的主要观点及中心主题;在本篇文章中,作者对所论述问题的态度及基本观点;

判断所阅读文章的体裁形式,例如:议论、寓言、科技、历史、讽刺、悲剧、喜剧、浪漫、科幻、恐怖、写实及诗歌;

作者在文章中所用的修辞手法的目的,在这篇文章中作者希望达到些什么;

作者通过特例、类比及比较想要说明些什么等等;

什么是文章中的基本事实;

阅读材料的含义或暗指是什么;

难词、偏词、怪词及多义词在这篇文章中的准确意思是什么等等。

对于上面所总结的SAT阅读选择题类型,大家如何在最短的时间内,正确选择答案呢?

首先快速浏览所有的所问问题,之后再有重点、有目的地通读全文;

对总结性、结论性、观点性及重要性的句子要特别注意,做出标识,在这类句子当中常常存在考题的答案;

在文章的第一段中,寻找文章的主要观点,同时对比文章的最后一段或接近文章结束的句子中所表述的中心思想,得出本文作者的基本观点;

考生在快速通读文章后,若无法一次性确定文章的中心主题,则需依据所问问题分段落、有重点地深入阅读。

【口语高分】雅思口语巧妙回答的4必杀技巧

雅思口语考试中,答题要有一定的技巧,虽然有着一定的难度,但是还是有技巧可循的,下面就跟着我们老师一起来看看。

【口语高分】雅思口语巧妙回答的4必杀技巧图1

答题时要往积极方面靠拢

在回答问题时应表现正面的态度。考生通常都应该诚实地回答所有问题,但有一些问题,回答的时候还是应该保持比较正面,尽量说好的一面。例如问你对自己家乡的印象,就算你真的认为非常不堪,也不应说出口。一句话,不要complain

回答需要直接清楚

千万不要刻意用一些深奥或复杂的字来解释事情。不要以为这样可以加深考官的印象,一个简洁明了的答案绝对比一个复杂难懂的答案好。但要指出的是,简单的答案并不等于短答案,答案太短会使整个面试有太多的停顿,而考官也要大伤脑筋多想问题,你面临的问题也就会更多。

把握好考场节奏

首先,你尽可能地多说,让考官少说,但也不要走上极端,把两个人的交谈变成一个人的演讲,要注意分寸。我们每一个考生并不应期望着考官会问到我们已准备的问题,但是如果遇到,不要word-for-word地把自己准备好的答案滔滔不绝地背诵出来,给人一种明显在背书的感觉。

巧用一些口语表达

Good morning.

Good afternoon.

I’m very well. Thank you. And you?

Pleased to meet you.

What exactly would you like to know?

As you can see from my CV…

Perhaps I can begin by telling you about…

以上就是我们为大家整理的关于雅思口语考试中的答题技巧介绍,希望大家看完有所了解!

【考场考点】沈阳师范大学外国语学院托福考点详情及考友考评分

今天小编这里为大家介绍一下辽宁省托福考点详情及评价。这里小编整理的是沈阳师范大学外国语学院托福考点,主要为大家罗列了沈阳师范大学外国语学院托福考点的联系方式以及考点评价,希望对大家了解这个考点有帮助。

【考场考点】沈阳师范大学外国语学院托福考点详情及考友考评分图1

托福考点评价:沈阳师范大学外国语学院

代码: STN80078A

地址: 辽宁省沈阳市皇姑区黄河北大街253号沈阳师范大学信息技术中心楼二层205房间.

代码: STN80078B

地址: 辽宁省沈阳市皇姑区黄河北大街253号沈阳师范大学信息技术中心楼二层203房间.

代码: STN80078C

地址: 辽宁省沈阳市皇姑区黄河北大街253号沈阳师范大学信息技术中心楼二层207房间.

邮编: 110034

交通路线: 236路,255路沈阳师范大学车站下车 . 沈阳地铁二号线到’师范大学’站下车

电话: 024-86593354

主页: www.lilyedu.com

住宿:

1、北门那边有很多小旅店,异乡缘挺不错的,有80、100、120的

2、离北门很近的地方有家金麟宾馆,标间是160元

3、如家酒店(北陵公园旁),酒店的隔音效果不是很好

考场情况:

显示器:方正纯平,非液晶

鼠标键盘:键盘鼠标很新

耳麦音质:耳麦是罗技的,隔音效果不错,可自己调节音量

隔板:没有隔板,但考位空间很大,四楼考场没隔板,每个人单独一桌

监考:老师态度很好,监考不严

备注:

1、可以写口语模板,老师一般不管

2、A是4楼。B是2楼,候考、存包、签保密协议都是在二楼,没有储物柜,建议不要带贵重的物品

3、中间休息使时间可以适当延长

4、稿纸不需要三张一起换

考友评价1:

我住在沈阳的同学家里,考试去和回是搭同学爸的车,所以这次关于住宿问题我就不太清楚了。

街道环境:不是非常好。刚刚入冬,沈阳很冷(我去过最北的地方),注意保暖。

学校环境:比街道好。进去后是在信息技术中心楼,其实就是电脑房的所在地。但是这个楼距离正门很远,而且背对正门,所以多问路人,越早找到越好。

进去是二楼。一楼有一些留学中介的给你塞东西。

写誓言和存东西是在大厅/走廊里,不是一个房间,人很多很吵,早早写好,存包是交给工作人员保管,他会给你一个牌号,吃的东西就放在写誓言的桌子上。厕所在走廊尽头。然后依旧在这个厅排队,一个个进去,拍照的地方就是考试房间。进去以后你会发现这个电脑房特大,并且没有隔间,只是独立座位。隔音效果基本没有。由于我是第一次考,所以无法完全投入,受的干扰更多了。由于是在一个没有隔音的大房间,所以口语答题此起彼伏,一定要全神贯注做自己的题。

考友评价2:

看到过一些介绍沈师B考场的帖子,都有些老了,而且就今天考试来看,和以前T友所描述有些差别,再加上太傻给了我很多帮助,回报下坛子。

B考场在二楼,存包和签到都是在考场右侧的一个大的走廊那,离考场很远,没影响。去那就被要求存包,只有吃的喝的能放在外面。所以想中间休息偷瞄JJ的还是别想了~厕所离考场也就几步远,出门十几秒的事。

存完包,签完到,拿着抄好的表,就能排队了。早排晚排一样,因为都是9:45统一解码(悲催的8:50就进场了,坐到9:45),个人觉得比较好,互相影响比较小,而且对偷听口语没有任何影响(后面叙述)。

进门先拍照,拍照在考场最前面,两个两个同时进行,最前面的几个座位(好像是21号),和另外几个可能会受到晚进考场同学的影响。证件查的不严,一道拍照的一个女生没带学生证也给考了。ETS给的那个什么准考证和号码都不用抄,不查。考场很大,差不多能做90-100人左右。电脑是方正的纯平,耳机是飞利浦的,戴着非常舒服(我差不多整个考试都带着,都没感到耳朵疼,下次买一个在寝室用==),隔音不错,应该是新的,键盘手感不错,总之除了屏幕占点地方,其他的条件不错。每个人之间没有隔断,但是两台机器之间隔了一个桌子多点的过道,只要你旁边的大哥口语不是靠吼得,戴着耳机几乎没有影响。起始发了5张粉色的稿纸,2个铅笔,话说铅笔上蛋疼的印着IELS(吐槽下…..ETS什么时候能出个自己的….)不够了可以找老师要。沈师外国语学院的老师监考,人都挺好,而且外院嘛,大家都知道,美女挺多的哦,今天就看到了个,考前养养眼也不错。

考场管的很松,甚至还有大哥十点多才进场的….==..,不过后进的,机器不够,都加到中间两排最后了,最后面的同学可能会有些影响。中间休息时间没有限制,吃完东西想进来就能进,进来之后,到10分钟了,也没人管你,可以坐在那听个够(前提是能听到,或者偷瞄到,前面的屏幕蛮容易看见的…)想考了,举手示意下,老师来给你解锁。

在路上

  两期夏令营的结束,结束的仅为两期夏令营而已,结束即是开始,对我,对夏令营的学生和其他老师,都一样。

  我的课,其实只有几句话:

  1.先不谈过去和未来,我们起码要知道,这一刻自己正在做什么。

  2.成为自己生命的掌坨人,而不是成为别人的木偶。

  3.如果你和大家付出的都一样,那么你和别人也没什么差别了,“一份耕耘一份收获”这话是有一定道理滴。

  4.考虑一下,做个被人记住的人。

  5.You are gonna

  be the worse or the best, but never in-between.

  6.切忌急功近利。

  7.最大的课堂是人生,而我们的老师则是我们一生中遇到的所有人。

  8.无论如何,不要后悔!今天你的努力,就是为了明天的不留遗憾,努力往前走吧!

  9.我说的只代表现在这刻的想法,不代表正确或以后不会改变,因为我也只是正在学习。

  我二十多天的课程里,只有那么几分钟的课是比较有价值的,但已经够了。

  带着中学时期的梦想,来到这里,把人生经历和体会分享给大家,以传播一点点信念。满心欢喜地回望站在6年前的自己,带着微笑着说声,“我做到了”。

  这就是我对过去的交代,接下来,我将带着现在的信念,继续往前走,走到什么时候什么地方,我不知道,只希望能够不让现在的自己失望。

【GRE填空尚方宝剑】2大复习攻略助你一臂之力

GRE填空破解方法,层出不穷,有难度的GRE考试试题,单词的使用与巨型的结构都相较于其他的考试有了一个本质的提升,所以,试它也更加难懂。但是,再难得语言,都有中心的表现,只要抓住中心便是做题的关键。下面就为大家揭秘GRE填空技巧,帮助大家顺利解决GRE填空难题。

【GRE填空尚方宝剑】2大复习攻略助你一臂之力图1

1.首先简化句子:

根据构造的成分,句子可以分成主干和修饰成分。主干是一个完整的主谓结构,而修饰成分可能是从句,定语或者状语。为了准确快速地理解句子的意义,你必须分析句子的结构。但有时你并不需要掌握句子的确切意义,因为有些句子逻辑关系极为明显,你只需通过这些揭示逻辑关系的过渡词或者语气词和理解其中的关键词就可以解题。

所以,很多时候你并不需要真正的掌握GRE填空每句话的句意,你只需将不可能包含过渡词和关键词的修饰成分略掉,这样可以帮助你快速地找到正确答案。

【GRE填空尚方宝剑】2大复习攻略助你一臂之力图2

2.然后,关注过渡词与关键词:

特别留意那些决定句子结构的过渡词,这些过渡词经常是连词,有时也会是语气态度词。通过它,你可以确定句子的组织形式(并列,或者转折),选择与之相匹配的词。

关键词是指那些决定句子内涵,正负态度和贬褒意义的词汇。一旦你识别了这些关键词,再由句子的构造的逻辑关系,空格的内容就显而易见。这里,最重要的是你对过渡词和关键词的敏感性。

很多考生非常不喜欢复杂的句型,那样会使理解文章很慌乱。两条简化复杂的规则,相信对GRE填空会有所帮助。所以,将难化简,将没有学过的学过的知识,是以上GRE填空技巧的中心思想。

【备考每日练】最新GRE填空题之_7

名师心血之作,考生必备最完美填空资料,让GRE填空更加完美,打造你的完美GRE分数,走过路过不要错过,命运掌握在自己手中,GRE掌握在自己手中,每日练一练,分数节节高,你值得拥有,且看且珍惜!GRE必胜!

【备考每日练】最新GRE填空题之图1

每日一练

Free trade is often praised as (i)_____for developingcountries’ economic
woes, but trade often also(ii)_____a country’s economy.

Blank(i) Blank(ii)

A.a panacea

B.a debacle

C.a euphemism

D.has an evanescent impact on

E.has deleterious effects on

F.brings unexpected benefits to

【备考每日练】最新GRE填空题之图2

正确答案

A E

题目解析

自由贸易经常被誉为灵丹妙药发展中国家的经济困境,但贸易往往对一个国家的经济也有不良影响

单词解释

a panacea 灵丹妙药

a debacle 一个失败

a euphemism 委婉说法

2015最新GRE填空每日一练(11月26日)

2015最新GRE填空每日一练(11月25日)

【必备资料】托福考试口语真题与范文——Which do you like to read

在初入托福备考的时候,很多学生当然会想要直观的感受一下托福口语究竟应该怎样的表达,同时,托福口语题目的出题也是有着一定的重复性的。想要取得托福的高分,真题的练习是有着一定的帮助的。那么,以下内容中我们就为大家带来托福考试口语真题与范文,希望能为大家带来帮助。

【必备资料】托福考试口语真题与范文——Which do you like to read图1

托福口语真题:

Describe a person that influenced you most.(06. 5.26; 06. 3. 17;06.10.22 考题;与 06.5.26 类似)

托福口语模板:

Sample answer:

The person that really influenced me most was Ms. Xing—my college teacher who taught us English literature.

Her class was quite different from the other teachers. In her class we were not expected to sit there and listen. We had to get more involved in the class activities, like discussions, comments or debates sometimes. Our creativity and imagination were developed enormously through the active participation.

On the other hand, she let us think more about life by sharing her experiences and more importantly, she taught me how to live on my own. So that’s why I was greatly influenced. Not only did she give me knowledge, but also she gave me courage and confidence as well.