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英語 高校生

左上の文で、orが繋いでいるのはa problemとwishesだと思ったのですが、正解はhasとwishesでした。なぜ前者の方ではダメなのですか?

⑩ 従属節は[]に入れて構造をつかめ 次の英文の下線部を訳しなさい The Western way of thinking is analytical. If a Westerner has a problem, or wishes to discuss a complex subject, he tries to analyse it. He tries to break the problem or the subject down into separate parts. putoinmos alumin しかし、 ① に if をつけて② に接続させ, 元の文に戻すと [If 〜] の部分は「もし~ なら」という条件を示す副詞 (主に動詞を修飾)の性格を持ちます。 このように副詞の 役割を持つ節を「副詞節」と言いますが, if がついたために,これ自体では独立した 文とは言えなくなってしまいましたね。いわば副詞に格下げされた節なので 「従属節」 と呼び,②は文として独立可能ですから 「主節」 と言います。 この「主節」と「従属 「節」の関係を図示すると,以下の3つのタイプになります。 toriita (1) [接続詞 + S + V + X], S + V + X. 例題のタイプ mogl (2) S+V+ X [接続詞 + S + V + X] . (桜美林大) 解 「節」――よく耳にする言葉ですね。 節は文の一部としてまとまった意味を表 法 それ自体の中に 「SV」 を含む単位を言うのでしたね。and, but, or, nor, for, so などを等位接続詞と呼び, その前後の節 (SVX) を等位節と言います。 SVX (等位節) / and SVX (等位節) 後、第2文 等位接続詞の前でピリオドを打つと,それぞれ独立した文になります。 一方, when, if, as, because, though などのほとんどの接続詞を従属接続詞と言いますが,な ぜ 「従属」と言うのでしょうか。 例題の下線部, 第2文で考えてみましょう。 [If a Westerner (接) もし~なら 西洋人が を持つある 問題 has a problem, S Vt 1 ~したいと思う or wishes について話し合う 複雑なテーマ <別文金) (to discuss a complex subject)], Vt 2 → (不) (Vt) (3) S+V, [接続詞 + S + V + X], X. S, [接続詞 + S + V + X], V + X. 「副詞」の性質から (3) のように,時には主節の中に割り込むタイプもあります。 こ の課のテーマは,このように副詞節を[ ]でくくり、主節と区別して修飾関係を つかむことです。 従属節 If ~ subject を [ ]でくくると,副詞としての文の一部になり, 主節の述 部を修飾していることがわかりますね。 第1文, 第3文については,従来通り前置詞句を( )でくくり, SV を決めて けば、簡単に文の骨格がつかめるはずです。 《全文訳〉 西洋の考え方は,分析的である。 もし西洋人がある問題を抱えたり, 複雑なテーマについて話し合いたいと思う場合は, (西洋人は) それを分析しよう とするのである。 その問題や課題を個々の部分に分解しようと努めるのである。 西洋人は~しようとする を分析しそれ he tries (to analyse it). S Vt 0 (不) (Vt) (0) 演習 10 次の英文の下線部を訳しなさい。 (解説・解答 別冊: p.6) [If ~ ] の部分からIf を除いてみましょう。 bans ai burois quibrell A Westerner has subject. (①) shioinobomeA となり, SVをそなえた独立した文ですね。一方, カンマ以下も独立した文です。 He tries to analyse it. (②) ニアークすると出産しない bran 分析する / break O down into N 「OをNに分解する 」 例題:語句 analytical 形分析的な/a complex subject 複雑なテーマ/ analyse [Vt] を When I speak of internationalization, I do not mean the changing of external life styles but the development of internal new attitudes. Our motivations must be in step with the conditions of the time. (大手前女子短大) 演習:語句 internationalization 图 国際化 / external 形外面上の/ internal 内面的 な / attitude 態度/motivation 動機づけ / in step with N 「Nと調和して」

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英語 高校生

四角2の8なぜto catchなのですか

20 ove. to be no 大学 Step 2 実践問題 First Stage Second Stage (答別冊 p.29) 1 イラストの内容に合うように,( )内の語を参考にして、英文を完成させなさい。 1) 2) (3) e's birt is said to about it h A 1) The woman doesn't mind 2) The man offered 3) The boy regretted in line for a while. (wait) 7 the elderly woman with the baggage. his umbrella. ② 次の文章を読み、()内の動詞を適切な形にしなさい。 (help) (bring) I have been on a dance team since I was in junior high school, so I'm used to '(dance) in front of others. I love to dance, but sometimes I have difficulty 2 (learn) new moves. When that happens, I practice 3 (dance) a lot with my teammates. I had a bad time once. I had to stop 4(dance) for a while because of a knee injury. I couldn't help 5 (cry) every day, but I tried be *positive. After (recover), I practiced hard again with the others. I'm proud of (do) so. NOTES positive 「前向きな」 catch up with ~ 「〜に追いつく」 3 次の日本文を英語に直しなさい。 catch up 今夜は勉強する気がしません。 I don't feel like studying tonight. 「動名詞 2 本日はパーティーにお招きいただき、ありがとうございます。 Thank you for inviting 3) 私は子どものころに、その動物園を訪れたことを覚えています。 4) 雪のために,その飛行機は離陸できなかった。 NOTES 4) 「離陸する」 take off Pome to the party today. (the snow を主語にして) Let's write about... 健康のためにいいと思うことを、動名詞を使って書いてみよう。 例) Having breakfast is good for your health. It gives you a lot of energy and gets you ready for the day. I also enjoy eating breakfast leisurely with my family on Sundays. 32 231

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英語 中学生

中3 英語 長文読解 問1 本文の内容から考えて、とありますがどこで判断して分かりますか?答えはウです

5 次の英文は, ジュディ (Judy) と健 (Ken) がボランティア活動をする (do volunteer work) ことについて対話しているもので す。 これを読んで問いに答えなさい。 Judy Ken, do you know children in the U.S. often do volunteer work? Ken: Oh, really? I didn't know about that. I'm interested in it, but I haven't ( ①) volunteer work yet. I want to know (1) Judy Well, in the U.S. they usually clean the parks and beaches, help at *animal shelters, or even read books to *elderly people in *nursing homes. Ken Great! I think we can do the same things in Japan. Judy: You're right. My mother and I like the animals at the zoo. A few years ago, we did volunteer work at the local zoo in my town. Ken: Really? I've never heard of ( 2 ) volunteer work at the zoo. What did you do there? Judy We helped to *prepare food for the animals and clean their *cages. Ken: I think you ( 3 ) a lot for the zoo. Judy: Yes. We also learned a lot about the animals. Ken: I think that was a good experience. I also like animals. So, I want to do some useful volunteer work at the zoo someday. Judy, in Japan, I've heard that *volunteers (help) local people after some of the serious *earthquakes since 2011. I think getting help from volunteers is a great help to them. Judy: Yes. (ways/to/are/many/help/there) other people. Ken: That's right. Oh, I remembered our *neighborhood association will have a cleaning day next weekend. I'll join it. Judy That's a good idea. We don't have such an event in U.S. Can I join you? Ken: Sure! We will start at 10 in the morning. Let's meet at Midori Park. Please bring some *work gloves. Judy : I see. ! (注) animal shelter (s) ・・・ 動物保護施設 ... elderly ... お年寄りの おり cage (s) volunteer (s) nursing homes ・・・ 高齢者福祉施設 ボランティアをする人 ... work gloves PF prepare... 〜の準備をする earthquake (s) ... neighborhood association J 問1 本文の内容から考えて,(1) (③)に入る語の組み合わせとして最も適当なものを, ア~エから選びなさい。 ア (1) do (2) did (3) done ウ (1) done 2 doing (3) did イ (1) did (2) done 3 doing I 1 doing (2) did done

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TOEIC・英語 大学生・専門学校生・社会人

この長文問題の答えと解説をお願いします。

15 語数: 398 語 出題校 法政大 5 We are already aware that our every move online is tracked and analyzed. But you 2-53 couldn't have known how much Facebook can learn about you from the smallest of social interactions - a 'like'*. (1) Researchers from the University of Cambridge designed (2) a simple machine-learning 2-54 system to predict Facebook users' personal information based solely on which pages they had liked. E "We were completely surprised by the accuracy of the predictions," says Michael 2-55 Kosinski, lead researcher of the project. Kosinski and colleagues built the system by scanning likes for a sample of 58,000 volunteers, and matching them up with other 10 profile details such as age, gender, and relationship status. They also matched up those likes with the results of personality and intelligence tests the volunteers had taken. The team then used their model to make predictions about other volunteers, based solely on their likes. The system can distinguish between the profiles of black and white Facebook users, 15 getting it right 95 percent of the time. It was also 90 percent accurate in separating males and females, Democrats and Republicans. Personality traits like openness and intelligence were also estimated based on likes, and were as accurate in some areas as a standard personality test designed for the task. Mixing what a user likes with many kinds of other data from their real-life activities could improve these predictions even more. 20 Voting records, utility bills and marriage records are already being added to Facebook's database, where they are easier to analyze. Facebook recently partnered with offline data companies, which all collect this kind of information. This move will allow even deeper insights into the behavior of the web users. 25 30 (3) - Sarah Downey, a lawyer and analyst with a privacy technology company, foresees insurers using the information gained by Facebook to help them identify risky customers, and perhaps charge them with higher fees. But there are potential benefits for users, too. Kosinski suggests that Facebook could end up as an online locker for your personal information, releasing your profiles at your command to help you with career planning. Downey says the research is the first solid example of the kinds of insights that can be made through Facebook. "This study is a great example of how the little things you do online show so much about you,” she says. "You might not remember liking things, " but Facebook remembers and (4) it all adds up.", * a 'like': フェイスブック上で個人の好みを表示する機能。 日本語版のフェイスブックでは「いいね!」 と表記される。 2-56 2-57 2-58 36

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