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English Senior High

あってますか?

A: Amy T: Taku JAOD Why were you エイミー: 拓, 大丈夫? どうして保健室に運ばれたの? taken to the nurse's office?pone T: I might have had heatstroke, but I feel better now. A: Please drink a lot of water. 1080 (E拓: 多分熱中症だったみたいだけど, 今は気分がよくなったよ。 T: Thanks. I'll be more careful next time. エイミー:たくさん水分とってね。 拓 ありがとう。 次はもっと気をつけるよ。 PT-OT.co マーク EXERCISES 1 日本語の意味に合うように,適切な語句を選びましょう。 id airlie erT 1. This picture (was painting/ was painted) by a famous painter. この絵は有名な画家によって描かれました。 doum 2. Kyoto is (visiting/ visited) by many foreign tourists. 京都は多くの外国人観光客に訪れられています。 出 3. The sea can't (be seen / see ) from this room. この部屋から海は見えません。 I norit eonob vetted o ai oxoY eno torit norit evianeque exom doum ai netuqma eint 2 日本語の意味に合うように,( )内の語句を並べかえましょう。 Four official languages (in / are / Singapore / spoken) are spoken in Singapore シンガポールでは4つの公用語が話されています。 The rock (is/moss / covered/with). is covered with moss その岩はコケでおおわれています。 This problem (be / in / discussed / should / the meeting) later. この問題は後ほど会議で話し合われるべきです。 should be discussed in the meeting LUCE meetingnetics 右の絵の場面に合うように、空所に入る語を考えましょう。 Lesson Excuse me, that seat ? ari a take the seat 「席をとる (座る)」 y in to divom feed artt nol yo al art (A 自分の住んでいる市町村にある建築物について, 発表しましょう。 Useful Words & Expressions p.80-H 例 In Yokohama, we have Yokohama Bay Bridge. It was built in 1989. It has been illuminated during the night since then.

Unresolved Answers: 1
English Senior High

あってますか?

生誕100周年なんだ。 H: You really like him! (@ 華 あなたって本当に手塚治虫が好きね R: That's right. I've heard that there were ロン:そうだよ。生誕90周年のときには many events on his 90th anniversary. H: Then, you'll be able to enjoy more events in 2028. heat. たくさんのイベントがあったって 聞いたことがあるよ。 華 : じゃあ、2028年はもっと イベントが楽しめるでしょうね。 EXERCISES (4) 日本語の意味に合うように、 適切な語句を選びましょう。 word evor WC 1. Annie (has / was) already cleaned the room. ied) for 20 years アニーはすでに部屋を掃除しました。 SOTHO (+[aor] ev 2. Miki (did not see / had never seen) snow before she moved to Sapporo.の 美樹は札幌に引っ越すまで雪を見たことがありませんでした。 3. The thief (had / has) already run away before the guards arrived. 泥棒は警備員が到着する前にすでに逃走していました。 oleow Jap sonia yhib had) long hair. Nobot moon ym benpelo IO 2 日本語の意味に合うように,( )内の語を並べかえましょう。 Sonimomval . (ever/have / ridden/you) a horse? ever riddenjoy borlanar 今までウマに乗ったことがありますか。 bean I have/mycar/repairin I haven't seen the movie Have you e . (haven't/I/ movie / seen / the) yet. I まだその映画を見ていません。 each other have/known/for/we years. (S) (before / had / her / I / seen), but I couldn't remember where. apr fuY ( 彼女を見たことがありましたが,どこだったのか思い出せませんでした。 I had seen her before 右の絵の場面に合うように、空所に入る語を考えましょう。 need bor S Have you ever seeh a kabuki performance? ORM emontempo verbom y ooled muori eevil yot gon 4 bron and bort erla eauboed benit 2DW Snol 聞いたことがある話やうわさについて, 友だちと対話しましょう。 ►Useful Words & Expressions pp.79- ony much

Unresolved Answers: 1
Chemistry Undergraduate

緊急です、!!!! この反応機構を矢印付きでお願いしたいです、、🥺

21:21 三 46 について | セクション 2.2 NeuroPコアの不斉合成 これ 林ピロリジン触媒存在下での9aの8への有機触媒マイケ ル付加反応とそれに続くアルデヒドの還元は、我々の以 前の報告 [26]と同様に行われ、2段階で89%の収率でアル コール7aが3:1のシン/アンチジアステレオマー混合物と して得られ、シン-7aで86%のee、 アンチ-7aで90%のee であった(図3)。 続いて、 キャンディらの条件下での 酸化Nef反応により、 87%という非常に良好な収率と16:1 のジアステレオマー比で二置換ラクトン11が得られ、 はDBU触媒による熱力学的平衡によってさらに濃縮され た。ラクトンをDIBAL-Hで還元してラクトール6aを得た 後、最初のウィッティヒ反応で開環し、アルコール12を 76%の収率で得た。塩基促進脱離副生成物13の生成を抑 制するために、徹底的な最適化が必要であったことを強 調しておくべきである。 最適化された拡張性と再現性を 備えた条件は、0℃でトルエン中の過剰量のメチル(トリ フェニルホスホニウム) 臭化物から生成したイリドの懸濁 液に6aをゆっくりと制御添加し、その後室温まで昇温す るというものである(詳細は補足情報の表S1およびS2を 参照)。 8 1.A (5mol.%), NO2 P-Nitrophenol (10 mol. %) THF, 15°C, 4 days 2. NaBH4, MeOH, 0 °C, 1 h 89% (two steps), syn/anti 3:1 OPMB 9a *NO2 + HO. HO. OPMB syn-7a anti-7a 86% ee NO2 OPMB 90% ee MePPh3Br, KHMDS Toluene 20°C to rt, 16 h NaNO2 AcOH DMF, 40°C, 16h 1.DBU (20mol.%.) HO THF, r.t., 16 h 2. DIBAL-H Toluene, 87%, trans/cis 16:1 OPMB OPMB 11 -78 to -50°C, 30 min 6a 97% (two steps) HO. HO -OPMB 12 76% スキーム3 13 9% OPMB A Ph Ph OTMS

Unresolved Answers: 0
TOEIC・English Undergraduate

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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