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生物 高校生

下の図における相対値というのはどういうことですか? お願いいたしますm(*_ _)m

●視細胞 視細胞には, 光を吸収する物質があり,これを視物質という。 視物質が光 を吸収すると,その構造が変化して、視細胞に受容器電位を生じさせる。 錐体細胞には青錐体細胞, 緑錐体細胞, 赤錐体細胞の3種類があり,それぞれ420 nm, 530nm, 560nm付近の波長の光を最もよ く吸収する異なった種類の視物質を含んでい おうはん macula retinae る(図2)。光を受容した錐体細胞の種類や割 合の情報を大脳で処理することによって, 色 は認識される。 錐体細胞は黄斑と呼ばれる網 膜の中央部に,特に多く分布している。また, 錐体細胞は弱い光では反応しないため,弱光 下では色を認識できない。 一方, 桿体細胞は, 黄斑をとりまく部分に多く分布し,弱い光で も反応する(図23)。 この細胞にはロドプシン と呼ばれる視物質があり 500nmの波長の 光を最もよく吸収する。 桿体細胞は,色の識 別に関与しない。 rhodopsin 光の吸収率(相対値) 青錐体細胞 100 50- 赤錐体細胞 細胞 緑錐体 0 400 450 500 550 600 650 光の波長 (nm) 細胞に含まれる視物質の種類によって 受容 する色が異なる。 図22 ヒトの錐体細胞の種類と光の吸収 (×104)16F 視細胞の数(個 8 桿体細胞 錐体細胞 mm² ← 鼻側盲黄 斑 耳側 図23 ヒトの網膜の視細胞の分布

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英語 高校生

四角IIの⑶なんでpressingなんですか 過去にしたことじゃなくないですか

EXERCISES UNIT7のまとめ いけないの。 (答 First Stage Second Stage Step 1 基本問題 別冊 p.28) Step 1 各文の( )内から最も適切なものを選びなさい。 1) I tried (to move, moving, move) that table, but it wouldn't 2) It's three o'clock now. What do you say (to take, to taken) a coffee break? 3) Please forgive me THOST First Sta move. taking, to be (not for attending, not to attend, for not attending) your lecture tomorrow. 2)に入る動詞を下の[]内から選び、適切な形にして入れなさい。 1) A: I'm really looking forward to ( B: Me, too. I can't wait. A: You should avoid )part in the race. )up late before an exam. B: I know. I'll go to bed early tonight. 3) A: This machine doesn't work. B: Try ( achine doesn the red button. 4) A: I must get up at six tomorrow morning. B: Remember ( ) the alarm clock before going to bed. [press/take/set/stay] JOJIW 3 日本文の意味に合うように,( )内に適語を入れなさい。 1)君のユニフォームはとても汚れているね。 洗濯が必要だ。 Your uniform is very dirty. It ( ) ( ) 2)昨日は折り返し電話できなくてごめんなさい。 O First Sta First Stage Second Stag I'm sorry for( ) ( ) ( ) you back yesterday. 3)妹は夜怖くて,一人でトイレに行けません。 My sister is afraid () ( ) to the bathroom alone at night. 日本文の意味に合うように,( の動詞は適切な形にすること。 )内の語句を並べかえなさい。 ただし、下線部 1)その映画はすばらしかった。 二度見る価値があるよ。 That movie was fantastic, It (twice, is, watch, worth). 2) 私たちはジュディが時間通りに来ないことに怒っていた。 We were angry at Judy (not, for, come) on time. 3)私は次に何をするべきかを言われるのは好きではない。 I don't (to, tell, do, what, like) next. First Stage AQUARIUM×ART atoa Let's write abou 230

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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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