而需求正是让我们感兴趣的地方。
图28突出显示了我们感兴趣的配置项。
对于这种情况，我们感兴趣的是动态缓存服务。
For this scenario, we are interested in the dynamic caching service.
当然，登录不成功，但是这不是我们感兴趣的。
Of course, the login will be unsuccessful, but that is not what you're interested in.
现在，我们感兴趣的是通过oreq返回的总数。
For now we are interested just in the sums that are returned via oreq.
即简易供稿，一个用来追踪我们感兴趣的一切事情的聚合工具。
An essential tool for keeping track of everything we aggregate is RSS, or Really Simple Syndication.
我们通常坐在父母的房间里读书、讨论我们感兴趣的问题。
We usually sit in my parents room, reading and discussing everything we're interested in.
我们感兴趣的是x除以,所以同时把分子分母除以n平方。
n We're interested in x divided by n. So let's divide both the top and the bottom by n squared.
当我们大家在讨论问题时，我们感兴趣的是去说，而不是倾听。
When we get into a discussion, we're not interested in listening, but speaking.
输出中最让我们感兴趣的是“r”、“po”和“id”字段。
What most interests us in the output are "r", "Po" and "id" fields.
对于模拟食品杂货店，我们感兴趣的进程是在通道处付款的顾客。
For the grocery store simulation, the process we are interested in is a customer who checks out at an aisle.
而这也正好是我们感兴趣的那组整数，现在，我们只需将它们相加。
This is exactly the set of integers we are interested in, so now we just need to add them.
我们感兴趣于是否能通过数字化来实现小额信贷，因为它本来就是严格的系统。
We were interested in whether it was possible to digitally enable microfinance, because it's actually kind of a tough system.
我们感兴趣的是30个最近的博客更新，而不是默认设置的20个条目。
We are also interested in the 30 most recent blog updates as opposed to the default setting of 20 entries.
步骤2：指定一个响应字符串数组，这些字符串的值都是我们感兴趣的。
Step 2: Specify an array of response strings whose values are of interest.
item元素的关键属性是name，用于查看我们感兴趣的字段值。
The key attribute for the item element is name and is used to check for the field values we are interested in.
以下代码展示了一个通过传入代码和我们感兴趣的服务ID调用此api的示例。
The code below shows an example of calling this API by passing in this and the service ID in which we are interested.
您将看到与以下清单2显示的代码相似的内容；我们感兴趣的是用粗体显示的那几部分。
You'll see something what's shown in Listing 2. We're interested in the parts in bold.
我们感兴趣的是构建一个报表，为每个销售区域内的所有客户检索2009年的所有产品销售。
We are interested in building a report retrieving all product sales for all customers within each sales region for 2009.
大多数的时候，我们仅仅对话语不感兴趣；我们感兴趣的是所述内容，也就是说，含义，主旨。
Most of the time, we aren’t interested in mere wording; we are interested in what was said, that is, meaning, the subject matter.
好，我们看最后的例子之前还有两件事情，第一是，我要提醒大家，我们感兴趣的是渐进的增长率。
Now. Two other things, before we do this last example. One is, I'll remind you, what we're interested in is asymptotic growth.
所以你们主要有，一个粒子的波动方程，我们的目的是考虑一个特殊的粒子，我们感兴趣的是电子。
So you're basically having a wave equation for a particle, and for our purposes we're talking about a very particular particle. What we're interested in is the electron.
我们很少会阅读由机器翻译过来的博客，就算博客里包含我们感兴趣并关注的话题，因为那种阅读体验太糟糕了。
Very few of us choose to read blogs - even on topics we enjoy and follow - via machine translation because the experience is so awkward.
第三个问题可能会使我们感兴趣，那确实使我们感兴趣，这就是：如果它能幸存，那能幸存多长时间呢？
Third question that might interest us, that does interest us, is this: If it survives, how long does it survive?
在这里我们感兴趣的只有两个参数，那就是LIBS和INC，它们提供了连接而且包括了编译器的参数。
The only two we're interested in here are LIBS and inc, which give the link and include parameters for the compiler.
我们需要获得一个服务引用，它可以让我们查看服务自身内部的属性，然后利用其来获得我们感兴趣的服务。
We need to get a service reference, which allows us to introspect properties of the service itself, and then use that to get the service that we're interested in.
在大多数情况下，我们并不需要关心它，所以我们还是看看我们感兴趣的东西：如何创建、保存和加载模型。
This doesn't concern us for the most part, so we'll leave it for the interesting bits: how to create, save, and load a model.
关系转换与其他映射不同，因为对于其他映射，我们感兴趣的是如何连接引用相同数据的不同属性名称或业务对象。
The relationship transform is different than other mappings because with other mappings we are interested in connecting different attribute names or business objects that refer to the same data.
关系转换与其他映射不同，因为对于其他映射，我们感兴趣的是如何连接引用相同数据的不同属性名称或业务对象。
The relationship transform is different than other mappings because with other mappings we are interested in connecting different attribute names or business objects that refer to the same data.
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