sentence muster

本文探讨了个人如何通过培养创新习惯来提升自我价值,强调了跳出固有思维模式的重要性。文章指出,面对社会压力和快速变化的世界,年轻人往往忽视了间隔年的价值;科学研究表明,我们可以通过有意识地培养新习惯来创造新的神经通路,从而实现思维创新。同时,文章提到了两个可能正在形成的社群:一个是学科导向的社群,专注于高度专业化的研究;另一个是问题导向的社群,倾向于在政策简报等场所发表研究成果。

1.   we become defensive when  criticised  and apply  negative  stereotypes to ohers

to boost  our  own esteem

2. devoted consertgoers who reply that recordings are no subtitute for live performance 

are missing the point

3. ants keep predatory  insects away from  where their  aphids feed ; Gmail  keeps the

 spammers out of our inboxes

4. at the same time , people continue to treate fire as an event  that  needs  to be wholly 

 controlled  and unleashed  only  out of necessity

5.  as  boards  scrutinize  succession plans  in  response to shareholder  pressure ,

 executives  who don`t get  the  nod  also may  wish  to  move on

6. everyone  needs  to find  their extra ----their unique value contribution   that  makes  them

  stand out  in  whatever is their  field  of  employment

7.  it is also the reason why when  we  try to describe  music with words ,all  we can do is articulate

 our  reactions to it  ,and not grasp music itself

8. scientists  jumped  to the rescue with some distinctly shaky evidence to the effect that  insects

would eat us up if birds failed to  contorl them

13.  the issue of voluntary part-time  relates to Obamacare because one of the main purposes was

to allow people to get insurance outsides of employment

22. the  researchers  mapped  not  only the city`s vast  and  ornate  ceremonial  areas  , but also  hundreds

of  simpier  apartment  complexes  where  common people  lived

23.  it may be said that the measure of the  worth  of any social  institution is  it`s  effect in  enlarging  and  improving

experience , but  this  effect  is  not a part of  its original  motive

24.  our mental health doesn`t  really  go  anywhere ; like  the  sun  behind  a  clound , it can  be  temporarily

hidden  from  view,  but  it  is  fully  capable  of  being  restored   in  an  instant

25.  the  most  loyal  customers  would still  get  the  product  they  favor 

 

 

59.Brain researchers have discovered that when we consciously develop new
habits,we create parallel synaptic paths,and even entirely new brain
cells,that can jump our trains of thought onto new,innovative tracks.

 

 

61 . In the past couple of weeks a quarrel has illustrated the value to advertisers

of such fine-grained information:Should advertisers assume that people are

happy to be tracked and sent behavioural ads?

 

 

69.  the company ,a major energy supplier in new england , proveked justified outrage in

vermoent last week when it  announced it was reneging on longstanding commitment to

abide by the strict nuclear regulations

 

70. Of all the changes that have taken place in English-language newspapers 

during the past quarter-century,perhaps the most far-reaching has been the
inexorable decline in the scope and seriousness of their arts coverage.

 

 

72. Scientists have found that although we are prone to snap overreactions,if

we take a moment and think about how we are likely to react,we can reduce
or even eliminate the negative effects of our quick,hard-wired responses.

 

 

 

76.  Today,widespread social pressure to immediately go to college in
conjunction with increasingly high expectations in a fast-moving world
often causes students to completely overlook the possibility of taking
a gap year.

77 . It could be that we are evolving two communities of social scientists:
one that is discipline-oriented and publishing in highly specialized
journals,and one that is problem-oriented and publishing elsewhere,
such as policy briefs.

 

 

78. steelworkers , airline emploryees , and  now  those   in the auto  industry  are

joining millions of  families  who  must  worry about interest  rates , stock  mark

fluctuation  and the harsh  reality  that they may  outive their retirement money

 

84.Yet,when one looks at the photographs of the garden created by 

the homeless,it strikes one that,for all their diversity of styles,these 

gardens speak of various other fundamental urges,beyond that of 

decoration and creative expression.

 

 

88. Calls to disassemble all telescopes on Mauna Kea or to ban future
development there ignore the reality that astronomy and Hawaiian
culture both seek to answer big questions about who we are,
where we come from and where we are going.

 

94. To encourage innovation and  competition , the  report  calls  for increased

investment  in  research ,the crafting  of  coherent curricula  that improve  students`

ability to solve  problems  and  communicate  effectively  in  the  21 st  century ,

increased  funding for teacher  and  the  encouragement   of  scholars  to  bring

their  learning to bear  on  the  great  challenges  of day

内容概要:本文详细介绍了“秒杀商城”微服务架构的设计与实战全过程,涵盖系统从需求分析、服务拆分、技术选型到核心功能开发、分布式事务处理、容器化部署及监控链路追踪的完整流程。重点解决了高并发场景下的超卖问题,采用Redis预减库存、消息队列削峰、数据库乐观锁等手段保障数据一致性,并通过Nacos实现服务注册发现与配置管理,利用Seata处理跨服务分布式事务,结合RabbitMQ实现异步下单,提升系统吞吐能力。同时,项目支持Docker Compose快速部署和Kubernetes生产级编排,集成Sleuth+Zipkin链路追踪与Prometheus+Grafana监控体系,构建可观测性强的微服务系统。; 适合人群:具备Java基础和Spring Boot开发经验,熟悉微服务基本概念的中高级研发人员,尤其是希望深入理解高并发系统设计、分布式事务、服务治理等核心技术的开发者;适合工作2-5年、有志于转型微服务或提升架构能力的工程师; 使用场景及目标:①学习如何基于Spring Cloud Alibaba构建完整的微服务项目;②掌握秒杀场景下高并发、超卖控制、异步化、削峰填谷等关键技术方案;③实践分布式事务(Seata)、服务熔断降级、链路追踪、统一配置中心等企业级中间件的应用;④完成从本地开发到容器化部署的全流程落地; 阅读建议:建议按照文档提供的七个阶段循序渐进地动手实践,重点关注秒杀流程设计、服务间通信机制、分布式事务实现和系统性能优化部分,结合代码调试与监控工具深入理解各组件协作原理,真正掌握高并发微服务系统的构建能力。
<think>根据上下文,用户输入了"sentence",但没有明确的问题。结合之前的对话历史,最后一次讨论是关于字符串全切分组合的问题,并且在相关问题中提到过处理结果中的句子(sentence)。因此,我推测用户可能是在询问关于之前代码中`sentence`变量的使用或相关解释。 但是,用户仅输入了“sentence”一词,可能希望了解在之前的全切分代码中`sentence`的作用,或者如何构建句子。因此,我将解释全切分代码中`sentence`的用途,并可能扩展关于字符串切分后句子构建的概念。 如果用户有更具体的需求,可能需要进一步澄清。但基于当前信息,我决定解释之前代码中的`sentence`变量,并给出一个更通用的句子构建示例。 ### 关于字符串全切分中的sentence变量解释 在之前的全切分代码中,`sentence`变量用于存储从当前切分位置到字符串末尾形成的子句(即由空格分隔的单词序列)。在递归过程中,我们将当前单词与后续切分结果(即子句)组合。 #### 代码回顾片段: ```python # 递归处理剩余部分 sub_sentences = dfs(end) # 获得从end位置开始的所有切分结果(列表形式) for sentence in sub_sentences: # 拼接当前单词和后续切分结果 if sentence: result.append(word + " " + sentence) else: result.append(word) ``` #### 解释: - `sub_sentences` 是从`end`索引开始向后切分的所有可能结果的列表。每个元素都是一个字符串,表示一种切分方案(由空格分隔的单词序列)。 - 当遍历`sub_sentences`时,`sentence`变量代表一种后续的切分方案(字符串)。 - 如果`sentence`非空(即还有单词),则将当前单词`word`和`sentence`用空格连接,形成一个新的句子。 - 如果`sentence`为空(表示已经到达字符串末尾),则只添加当前单词`word`。 #### 示例说明: 对于输入字符串`"dog"`和字典`["dog"]`: - 当递归到末尾时,`dfs(len("dog"))`返回`[""]`(表示一个空句子)。 - 那么对于单词`"dog"`,会进入`else`分支,将`"dog"`添加到结果中。 ### 通用句子构建示例 假设我们有一个单词列表,如何将它们构建成一个句子(字符串)。 ```python # 示例1: 使用空格连接单词列表 words = ["I", "love", "Python"] sentence = " ".join(words) print(sentence) # 输出: I love Python # 示例2: 处理可能为空的单词列表 words = [] sentence = " ".join(words) # 输出空字符串 print(sentence) # 示例3: 自定义连接方式 words = ["Hello", "world", "!"] sentence = "".join(words) # 输出: Helloworld! # 或者添加标点 sentence = " ".join(words) # 输出: Hello world ! ``` #### 在递归构建中的应用 在深度优先搜索中,我们通常需要将当前步骤的结果与递归返回的结果组合。上面全切分代码中的`sentence`就是递归返回的后续部分,我们将其与当前单词连接形成完整的句子。 ### 注意事项 - 在递归组合时,要注意边界情况(如递归到末尾时返回空列表或空字符串)。 - 连接操作可能因需求不同而不同(例如,用空格、逗号或其他分隔符)。 如果用户的问题不仅仅是解释`sentence`,而是想了解如何生成句子或其他相关内容,我们可以进一步扩展。 §§相关问题§§: 1. 在递归回溯中如何高效地构建字符串? 2. 除了空格,如何处理不同的分隔符(如逗号)? 3. 如果切分结果需要包含标点符号,应如何修改代码? 4. 如何避免全切分组合中的重复计算(记忆化优化)? </think>### Python 中 `sentence` 的处理与操作详解 `sentence`(句子)在编程中通常指代文本字符串的处理单元。以下是关于句子处理的常见操作和解决方案: #### 1. 基础句子操作 ```python sentence = "The quick brown fox jumps over the lazy dog" # 获取句子长度 print(len(sentence)) # 输出: 43 # 句子拆分(单词级) words = sentence.split() print(words) # ['The', 'quick', 'brown', 'fox', 'jumps', 'over', 'the', 'lazy', 'dog'] # 句子拼接 new_sentence = " ".join(["Hello", "world", "!"]) print(new_sentence) # Hello world ! ``` #### 2. 高级句子处理(包含 NLP) ```python import spacy # 加载英文模型 nlp = spacy.load("en_core_web_sm") def analyze_sentence(text): """深入分析句子结构""" doc = nlp(text) # 提取关键信息 results = { "tokens": [(token.text, token.pos_) for token in doc], "entities": [(ent.text, ent.label_) for ent in doc.ents], "sentiment": doc.sentiment if hasattr(doc, 'sentiment') else "N/A" } return results # 使用示例 analysis = analyze_sentence("Apple Inc. is planning to open a new store in Paris next month.") print(analysis["tokens"]) # 词性标注 print(analysis["entities"]) # 命名实体识别 ``` #### 3. 句子生成(模板与 AI) ```python # 使用模板生成句子 def generate_sentence(template, **kwargs): return template.format(**kwargs) print(generate_sentence("{subject} {verb} {object}", subject="The cat", verb="chased", object="the mouse")) # 输出: The cat chased the mouse # 使用 Transformers 生成句子 from transformers import pipeline generator = pipeline('text-generation', model='gpt2') generated = generator("In a surprising turn of events,", max_length=50, num_return_sequences=2) for seq in generated: print(seq['generated_text']) ``` #### 4. 句子验证与清洗 ```python import re def clean_sentence(sentence): """清洗句子:移除多余空格、纠正标点""" # 移除首尾空格 sentence = sentence.strip() # 标准化空格 sentence = re.sub(r'\s+', ' ', sentence) # 确保句末有标点 if not sentence.endswith(('.', '!', '?')): sentence += '.' return sentence dirty_sentence = " Hello world this is messy " print(clean_sentence(dirty_sentence)) # "Hello world this is messy." ``` #### 5. 多语言句子处理 ```python import langid from googletrans import Translator def detect_and_translate(text, target='en'): """检测语言并翻译句子""" # 检测语言 lang, _ = langid.classify(text) # 翻译 translator = Translator() translation = translator.translate(text, src=lang, dest=target) return { "original_lang": lang, "translated_text": translation.text } print(detect_and_translate("Bonjour le monde", "zh-CN")) # {'original_lang': 'fr', 'translated_text': '你好世界'} ``` ### 关键概念解释: 1. **分词(Tokenization)**:将句子拆分为单词或子词单元 2. **词性标注(POS Tagging)**:识别单词在句子中的语法角色 3. **命名实体识别(NER)**:识别文本中的专有名词(人名、地名等) 4. **情感分析**:判断句子的情感倾向 5. **机器翻译**:在不同语言间转换句子
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