84消毒液是一种有刺激性气味的高效液体消毒剂．主要成分为次氯酸钠（NaClO），广泛用于宾馆、旅游、医院、食品加工、家庭等的卫生消毒．请阅读信息并回答：

（1）次氯酸钠的制取原理是氯气与氢氧化钠反应生成氯化钠，次氯酸钠和水，化学反应方程式为　____ ；

（2）消毒液中次氯酸钠自身没有消毒作用，有消毒作用的是次氯酸钠与空气中二氧化碳反应得到的次氯酸（HClO），化学方程式为　____　；

（3）84消毒液是含氯消毒剂，氯气是一种挥发性的有毒气体，因此，84消毒液必须____保存．

阅读下列短文，从每题所给的四个选项中，选出最佳选项。

The health-care economy is filled with unusual and even unique economic relationships. One of the least understood involves the peculiar roles of producer or “provider” and purchaser or “consumer” in the typical doctor-patient relationship. In most sectors of the economy, it is the seller who attempts to attract a potential buyer with various appealing factors of price, quality, and use, and it is the buyer who makes the decision. Such condition, however, is not common in most of the health-care industry.

In the health-care industry, the doctor-patient relationship is the mirror image of the ordinary relationship between producer and consumer. Once an individual has chosen to see a physician — and even then there may be no real choice — it is the physician who usually makes all significant purchasing decisions: whether the patient should return “next Wednesday”, whether X-rays are needed, whether drugs should be prescribed, etc. It is rare that a patient will challenge such professional decisions or raise in advance questions about price, especially when the disease is regarded as serious.

This is particularly significant in relation to hospital care. The physician must certify the need for hospitalization, determine what procedures will be performed, and announce when the patient may be discharged. The patient may be consulted about some of the decisions, but in general it is the doctor's judgments that are final. Little wonder then that in the eye of the hospital it is the physician who is the real “consumer”. As a consequence, the medical staff represents the “power center” in hospital policy and decision-making, not the administration.

Although usually there are in this situation four identifiable participants— the physician, the hospital, the patient, and the payer (generally an insurance carrier or government) — the physician makes the essential decisions for all of them. The hospital becomes an extension of the physician; the payer generally meets most of the bills generated by the physician/hospital, and for the most part the patient plays a passive role. We estimate that about 75-80 percent of health-care choices are determined by physicians, not patients. For this reason, the economy directed at patients or the general is relatively ineffective.

如图，小华用不计重力的弹簧测力计拉着一物块以2 m/s的速度在水平地面上匀速前进，弹簧测力计的读数为____N，物块受到的滑动摩擦力的大小为 ____N；当速度增加到4 m/s时，物块受到的滑动摩擦力的大小为 ____N

    AlphaGo is a computer program that plays the board game Go.

    In March, 2016, the pride of humankind was crushed (粉碎) by a computer. Google's AlphaGo defeated the South Korean grandmaster (围棋大师) Lee Sedol four games to one, as the world looked on with shock and awe (敬畏). Artificial intelligence (AI, 人工智能) had suddenly reached a new and unexpected height.

    But as smart as AlphaGo is, it's no longer the best Go “player” in the world. Google's artificial intelligence group, DeepMind, has created the next generation of its Go-playing program, called AlphaGo Zero. The new AI program is unique in the way it learned to play Go. Instead of learning from thousands of human matches, as its predecessor (前任) did, AlphaGo Zero mastered Go in just two days without any human knowledge of the game and defeated AlphaGo by day three, reported The Guardian. It then went on to defeat AlphaGo 100 games to zero.

    To learn how to play Go, AlphaGo Zero played millions of matches against itself using only the basic rules of the game to rapidly create its own knowledge of it. Like the previous version, it used “reinforcement (增强) learning to become its own teacher,” according to DeepMind's website.

    “It's more powerful than previous approaches,” David Silver, AlphaGo's lead researcher, told The Guardian, “because by not using human data, or human expertise in any fashion, we've removed the constraints (约束) of human knowledge and it is able to create knowledge itself.”

    AlphaGo Zero's approach to self-learning is a significant advancement in AI that could be applied to help solve some of the world's biggest problems, according to a recent research report published in the journal Nature. For example, DeepMind co-founder Demis Hassabis argues that AlphaGo Zero could probably find cures for a number of serious diseases within weeks, according to The Telegraph. Indeed, the AI is now being used to study protein folding, which is connected to diseases such as Parkinson's and Alzheimer's.

    So now that AI has exceeded (超过) the bounds of human knowledge, perhaps the question is not about what AI can learn from humans, but what humans can learn from AI. We can only wait and see.