If we calculate the change in entropy during gas mixing, we will find that this quantity is positive.
如果我们计算气体混合过程中熵的变化，我们会发现这个量是正的。
A score function for optimization based on maximum mutual information entropy with odditional restriction is proposed.
提出了基于最大互信息熵且具有奇数约束的优化得分函数。
All driven by entropy of mixing.
所有这些都是由混合熵引起的。
So that's our entropy of mixing.
那就是我们混合物的熵。
Entropy of mixing comes in here.
熵从这来。
Just from the entropy of mixing.
因为混合熵。
They're in your notes for entropy.
它们在你们关于熵的笔记中。
但是熵也会起作用。
Do systems like to have more entropy?
对吗？体系是不是倾向于具有更多的熵？
That's entropy and the arrow of time.
这就是熵和时间之箭。
熵增加。
And it's all driven by entropy of mixing.
这些的基本原因都是熵的混合。
It's all entropy that's driving the mixture.
只有熵在驱动这个混合过程。
Entropy is the tendency of things to disorder.
熵是指物体失序的趋势。
Any questions about these entropy driven cases?
关于这些熵驱动的例子有什么问题吗？
And continue to derive the macroscopic entropy changes.
继续得到宏观的熵变。
So we can just explicitly calculate the entropy of mixing.
这样我们能更明确地,计算混合后的熵。
This is the entropy, or disorder, arising from your search.
这就是由于你的搜索引发的熵，也就是无序状态。
Ultimately. And other things, but entropy is very important.
最后，还有其它一些东西，但熵是非常重要的。
The entropy of mixing of reactants and products wasn't there.
没有反应物和生成物的熵。
Because you've got entropy of mixing happening in all of this.
因为我们得到的是所有这些混合的熵。
In a formal sense, transreption removes entropy from resources.
从某种意义上说，transreption移除了资源的熵。
Without entropy of mixing, we would be sitting on this curve here.
没有混合熵，我们得到的就是这条曲线。
We're building up to entropy and to engines, Carnot cycles, etcetera.
我们要研究，熵，热机，卡洛循环等概念。
Specifically, how entropy of mixing really becomes key to equilibrium.
特别地，为什么熵的混合，对于平衡态如此重要。
This seems incompatible with our experience of how entropy increases.
这似乎与我们已知的一致性增加的经验不符合。
So now I've got the entropy of mixing even in a condensed phase the liquid.
那么现在我们已经得到混合物的熵，即使对相对浓缩的液相。
Without entropy of mixing, then everything would go directly to the products.
没有混合熵的话，所有的东西都会变成产物。
Entropy is just a measure of how disorderly things are. And it tends to grow.
熵是对无序程度的一个度量，而且熵往往是增加的。
Entropy is just a measure of how disorderly things are. And it tends to grow.
熵是对无序程度的一个度量，而且熵往往是增加的。
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