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生物 高校生

(イ)Aとaの遺伝子頻度がそれぞれ0.9と0.1というのは数が A:a=9:1ということではないのでしょうか? 私のノートに書いたこのやり方ではなぜ解けないのですか?

(22. 共通テスト本試改題) 思考 4. 自由交配と自家受精個体数が減少すると近親交配の機会が増して, 生まれてくる 子の生存率や成長速度が低下することがある。 これは,低頻度で存在する潜性の有害なア レルがホモ接合になることで起こる。 近親交配が生じるとホモ接合体が増えることは,中 立なアレルを用いて確かめることができる。 自家受精によるホモ接合体の頻度の変化に関 する次の文章中のアイに入る数値の組合せとして最も適当なものを,後の①~⑧のうち から1つ選べ。 知合 まず,自由に交配が行われている個体群を考え, 1組のアレルAとa (A は aに対して顕 性)を含む遺伝子座において、 潜性のホモ接合体の頻度が1%であるとする。このとき, ヘテロ接合体 Aaの頻度は(ア)%である。 ここで, すべての個体が自家受精によって 等しい数の子を次世代に残すとすると, aa の個体が次世代に残す子の遺伝子型はすべて aa となるが, Aa の個体が残す子の4分の1もaaとなる。 したがって, 次世代における aaの頻度は(イ)%と求められ, 自由に交配が行われていた親世代に比べて頻度が高ま る。 アイ ア ① 1.98 1.495 (5) 18 4.5 ② 1.98 2.495 ⑥ 18 5.5 ③ 9 2.25 ⑦ 54 13.5 49 3.25 8 54 14.5 さ 問 (22. 共通テスト追試改題) ・対策 313

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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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