2005英语一text1

Everybody loves a fat pay rise. Yet pleasure at your own can vanish if you learn that a colleague has been given a bigger one. Indeed, if he has a reputation for slacking, you might even be outraged. Such behaviour is regarded as “all too human,” with the underlying assumption that other animals would not be capable of this finely developed sense of grievance. But a study by Sarah Brosnan and Frans de Waal of Emory University in Atlanta, Georgia, which has just been published in Nature, suggests that it is all too monkey, as well.

The researchers studied the behaviour of female brown capuchin monkeys. They look cute. They are good-natured, co-operative creatures, and they share their food readily. Above all, like their female human counterparts, they tend to pay much closer attention to the value of “goods and services” than males.

Such characteristics make them perfect candidates for Dr. Brosnan’s and Dr. de Waal’s study. The researchers spent two years teaching their monkeys to exchange tokens for food. Normally, the monkeys were happy enough to exchange pieces of rock for slices of cucumber. However, when two monkeys were placed in separate but adjoining chambers, so that each could observe what the other was getting in return for its rock, their behaviour became markedly different.

In the world of capuchins, grapes are luxury goods (and much preferable to cucumbers). So when one monkey was handed a grape in exchange for her token, the second was reluctant to hand hers over for a mere piece of cucumber. And if one received a grape without having to provide her token in exchange at all, the other either tossed her own token at the researcher or out of the chamber, or refused to accept the slice of cucumber. Indeed, the mere presence of a grape in the other chamber (without an actual monkey to eat it) was enough to induce resentment in a female capuchin.

The researchers suggest that capuchin monkeys, like humans, are guided by social emotions. In the wild, they are a co-operative, group-living species. Such co-operation is likely to be stable only when each animal feels it is not being cheated. Feelings of righteous indignation, it seems, are not the preserve of people alone. Refusing a lesser reward completely makes these feelings abundantly clear to other members of the group. However, whether such a sense of fairness evolved independently in capuchins and humans, or whether it stems from the common ancestor that the species had 35 million years ago, is, as yet, an unanswered question.

  1. In the opening paragraph, the author introduces his topic by ________.

[A] posing a contrast

[B] justifying an assumption

[C] making a comparison

[D] explaining a phenomenon

  1. The statement “it is all too monkey” (Last line, Paragraph l) implies that ________.

[A] monkeys are also outraged by slack rivals

[B] resenting unfairness is also monkeys’ nature

[C] monkeys, like humans, tend to be jealous of each other

[D] no animals other than monkeys can develop such emotions

  1. Female capuchin monkeys were chosen for the research most probably because they are ________.

[A] more inclined to weigh what they get

[B] attentive to researchers’ instructions

[C] nice in both appearance and temperament

[D] more generous than their male companions

  1. Dr. Brosnan and Dr. de Waal have eventually found in their study that the monkeys ________.

[A] prefer grapes to cucumbers

[B] can be taught to exchange things

[C] will not be co-operative if feeling cheated

[D] are unhappy when separated from others

  1. What can we infer from the last paragraph?

[A] Monkeys can be trained to develop social emotions.

[B] Human indignation evolved from an uncertain source.

[C] Animals usually show their feelings openly as humans do.

[D] Cooperation among monkeys remains stable only in the wild.

基于径向基函数神经网络RBFNN的自适应滑模控制学习(Matlab代码实现)内容概要:本文介绍了基于径向基函数神经网络(RBFNN)的自适应滑模控制方法,并提供了相应的Matlab代码实现。该方法结合了RBF神经网络的非线性逼近能力和滑模控制的强鲁棒性,用于解决复杂系统的控制问题,尤其适用于存在不确定性和外部干扰的动态系统。文中详细阐述了控制算法的设计思路、RBFNN的结构与权重更新机制、滑模面的构建以及自适应律的推导过程,并通过Matlab仿真验证了所提方法的有效性和稳定性。此外,文档还列举了大量相关的科研方向和技术应用,涵盖智能优化算法、机器学习、电力系统、路径规划等多个领域,展示了该技术的广泛应用前景。; 适合人群:具备定自动控制理论基础和Matlab编程能力的研究生、科研人员及工程技术人员,特别是从事智能控制、非线性系统控制及相关领域的研究人员; 使用场景及目标:①学习和掌握RBF神经网络与滑模控制相结合的自适应控制策略设计方法;②应用于电机控制、机器人轨迹跟踪、电力电子系统等存在模型不确定性或外界扰动的实际控制系统中,提升控制精度与鲁棒性; 阅读建议:建议读者结合提供的Matlab代码进行仿真实践,深入理解算法实现细节,同时可参考文中提及的相关技术方向拓展研究思路,注重理论分析与仿真验证相结合。
评论
成就一亿技术人!
拼手气红包6.0元
还能输入1000个字符
 
红包 添加红包
表情包 插入表情
 条评论被折叠 查看
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值