quantitating

简明释义

英[kwɒn.tɪ.teɪt]美[kwɑːn.tɪ.teɪt]

vt. 测定（或估计）……的数量；用数量表示（quantitate 的现在分词）

英英释义

单词用法

同义词

反义词

例句

1.The new models are very useful for detecting and quantitating small lung metastasis in a objective way, and the abdomen metastasis could be quantitated now.

而利用表达荧光蛋白的新模型就可以比较准确方便地对肺和腹腔转移灶进行定量。

2.The new models are very useful for detecting and quantitating small lung metastasis in a objective way, and the abdomen metastasis could be quantitated now.

而利用表达荧光蛋白的新模型就可以比较准确方便地对肺和腹腔转移灶进行定量。

3.Objective:To Assess the diagnostic value of Doppler power tissue imaging(DPTI) on Quantitating the endocardial size of infarct myocardium.

目的：探讨多普勒能量组织成像技术（DPTI）定量梗死心肌内膜面积的价值。

4.The retina was sectioned for counting the cells in the ganglionic layer of the optic nerve and quantitating optic nerve lesion.

然后进行视网膜切片，计数视神经节细胞层细胞，定量视神经损伤。

5.She is skilled at quantitating 量化 customer satisfaction through surveys.

她擅长通过调查对客户满意度进行量化。

6.The study aims at quantitating 量化 the environmental impact of plastic waste.

该研究旨在对塑料废物的环境影响进行量化。

7.The team is quantitating 量化 the amount of carbon emissions produced by the factory.

团队正在对工厂产生的碳排放量进行量化。

8.Researchers are quantitating 量化 the effects of the new drug on cancer cells.

研究人员正在对新药对癌细胞的影响进行量化。

9.The laboratory is focused on quantitating 量化 the levels of various proteins in the sample.

实验室专注于对样本中各种蛋白质水平的量化。

作文

In the field of scientific research, data plays a crucial role in validating hypotheses and drawing conclusions. One of the key processes involved in this is the act of quantitating 量化 various parameters and variables. This process allows researchers to convert qualitative observations into numerical values, making it easier to analyze and interpret data. For instance, in a study examining the effects of a new drug on blood pressure, researchers must quantitate 量化 the changes in systolic and diastolic pressures before and after treatment. The importance of quantitating 量化 data cannot be overstated. It provides a common framework for understanding complex phenomena. When scientists quantitate 量化 their findings, they can compare results across different studies and populations, which enhances the reliability of their conclusions. In addition, quantitating 量化 allows for statistical analysis, enabling researchers to determine the significance of their results and to identify trends and patterns that may not be immediately apparent from qualitative observations alone.Moreover, quantitating 量化 is not limited to the natural sciences. In social sciences, for example, researchers often use surveys and questionnaires to gather data, which they then quantitate 量化 to analyze public opinion or behavioral patterns. By assigning numerical values to responses, researchers can apply statistical methods to draw meaningful conclusions about societal trends.In recent years, advancements in technology have facilitated the quantitating 量化 of data on an unprecedented scale. Big data analytics, machine learning, and artificial intelligence have transformed how we approach data collection and analysis. These technologies allow for real-time quantitation 量化 of vast amounts of information, providing insights that were previously unattainable. For example, social media platforms quantitate 量化 user interactions to understand engagement levels and improve user experience.However, it is essential to recognize that quantitating 量化 data comes with its challenges. The accuracy of quantitation 量化 depends on the methods used and the quality of the data collected. Poorly designed studies or biased data can lead to misleading results. Therefore, researchers must be diligent in their approach to quantitating 量化 data, ensuring that they use appropriate methodologies and statistical tools.In conclusion, quantitating 量化 is a fundamental aspect of research across various disciplines. It enables researchers to transform qualitative insights into quantitative data, facilitating rigorous analysis and comparison. As technology continues to evolve, the ability to quantitate 量化 data will become even more critical in our quest to understand the world around us. By embracing the principles of quantitation 量化, researchers can contribute to a more accurate and comprehensive body of knowledge, ultimately benefiting society as a whole.

在科学研究领域，数据在验证假设和得出结论中发挥着至关重要的作用。其中一个关键过程就是对各种参数和变量进行量化。这个过程使研究人员能够将定性观察转化为数值，使数据的分析和解释变得更加容易。例如，在一项研究中，研究人员必须对治疗前后收缩压和舒张压的变化进行量化。量化数据的重要性不言而喻。它为理解复杂现象提供了一个共同的框架。当科学家们对自己的发现进行量化时，他们可以比较不同研究和人群的结果，从而增强结论的可靠性。此外，量化也允许进行统计分析，使研究人员能够确定结果的显著性，并识别可能并不明显的趋势和模式。此外，量化不仅限于自然科学。在社会科学中，例如，研究人员通常使用调查和问卷收集数据，然后对其进行量化以分析公众舆论或行为模式。通过为响应分配数值，研究人员可以应用统计方法得出关于社会趋势的有意义的结论。近年来，技术的进步使得数据的量化达到了前所未有的规模。大数据分析、机器学习和人工智能改变了我们对数据收集和分析的方式。这些技术允许实时量化大量信息，提供以前无法获得的见解。例如，社交媒体平台量化用户互动，以了解参与水平并改善用户体验。然而，必须认识到，量化数据也面临挑战。量化的准确性取决于所使用的方法和收集数据的质量。设计不当的研究或偏见的数据可能导致误导性的结果。因此，研究人员必须在量化数据的过程中保持谨慎，确保使用适当的方法和统计工具。总之，量化是各个学科研究的基本方面。它使研究人员能够将定性见解转化为定量数据，从而促进严格的分析和比较。随着技术的不断发展，量化数据的能力在我们理解周围世界的追求中将变得更加重要。通过接受量化的原则，研究人员可以为更准确和全面的知识体系做出贡献，最终造福整个社会。