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细说电子垃圾

①随着高新技术的迅猛发展,电子产品更新换代的周期越来越短,这也使得世界上报废或“被报废”的各类计算机、手机、家用电器等电子垃圾增量惊人。目前全世界每年产生的电子垃圾正以18%的速度增长。据有关部门预测,到2017年,全球产生的电子垃圾总量可能会增长至6540万吨。

②有研究表明,电子垃圾蕴含着巨大价值。废旧电器电子产品里贵金属的含量往往比矿石更高。例如,一吨电路板包含的金是一吨金矿石的40-800倍。一吨废旧线路板可提取400克黄金、200千克铜及500克其他贵金属。

③在暴利驱使下,我国电子垃圾加工小作坊遍地开花。从表面上看,这是在“炼金”,实际上,电子垃圾已成为继工业时代化工、冶金、造纸等废弃物污染后又一新的环境杀手。

④为什么这样说呢?

⑤电子垃圾含有汞、铬、镉、铅等多种重金属,这些重金属很难分解。在电子垃圾处理过程中,重金属会进入土地或水源中,人体吸收后会与体内的蛋白质及酶发生反应,使蛋白质及酶失去活性,甚至有些重金属会在人体某些器官聚集,一旦超过了人体所承受的极限,人体就会发生各种重金属中毒。

⑤电子垃圾很多采用塑料或新型塑质材料作外壳,这些材料不易降解,危害巨大,直接抛弃到陆地或水中的塑料,有时候会被动物误食,导致这些动物肉质有毒或大量死亡;埋藏在土地中的塑料会影响土质和土地肥力,导致土质松软或污染地下水;如果直接焚烧塑料,则会产生大量的有害气体,严重污染空气。

⑦电子垃圾中的各种阻燃剂、溶剂都是化学污染的重要。有些化学药剂天然具有毒性,有的可能诱发癌症等人体病变。

⑧电子垃圾造成的危害在我国一些地方已经显现,必须引起高度的关注和警惕,在回收电子垃圾方面,我们可以学习和借鉴发达国家已有的可行的制度与经验。

⑨在欧洲,德国对电子垃圾的回收处理堪称典范,制度规范和技术均较为发达。早在1991年,德国就颁布了欧洲第一个专门处理电子垃圾的法律——《电子废弃物法规》。1996年德国公布了更为系统的《循环经济和废物管理法》。德国在电子垃圾回收方面走在了欧洲的前列,它利用各市区直属的市政企业对电子垃圾进行回收,提供网络化服务,上门为消费者收集废旧电器。德国废旧电器回收厂普遍采用一种电子破碎机来分选废旧电器中的有用物和废物,分选出来的金属会根据含金量再转售给终端处理厂,其废旧电器的回收再利用率达90%以上。

⑩面对电子垃圾给我国生态环境和居民健康带来的严重危害,我国必须从法律制度建设、电子废弃物体系化管理等方面着手,积极行动,采取多管齐下的强力应对措施,全力阻止电子垃圾对环境的破坏。

⑪2014年,环保部启动了电子废物无害化处理项目。该项目的实施将推动我国电子废物环境无害化管理体系和技术标准体系的完善,以减少持久性有机污染物的排放。

    (本文有删改)

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    Computers have beaten human world champions at chess and, earlier this year, the board game Go. So far, though, they have struggled at the card table. So we challenged one AI to a game.

    Why is poker(扑克)so difficult? Chess and Go are “information complete” games where all players can see all the relevant information. In poker, other players' cards are hidden, making it an “information incomplete” game. Players have to guess opponents' hands from their actions----tricky for computers. Poker has become a new benchmark for AI research. Solving poker could lead to many breakthroughs, from cyber security to driverless cars.

    Scientists believe it is only a matter of time before AI once again vanquishes humans, hence our human-machine match comes up in a game of Texas Hold's Em Limit Poker. The AI was developed by Johannes Heinrich, researcher studying machine learning at UCL. It combines two techniques: neural(神经的)networks and reinforcement learning(强化学习).

    Neural networks, to some degree, copy the structure of human brains: their processors are highly interconnected and work at the same time to solve problems. They are good at spotting patterns in huge amounts of data. Reinforcement learning is when a machine, given a task, carries it out, learning from mistakes it makes. In this case, it means playing poker against itself billions of times to get better.

    Mr Heinrich told Sky News: “Today we are presenting a new procedure that has learned in a different way, more similar to how humans learn. In particular, it is able to learn abstract patterns, represented by its neural network, which allow it to deal with new and unseen situations.”

    After two hours of quite defensive play, from the computer at least, we called it a draw.