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相关概念视频

Prevalence and Incidence01:08

Prevalence and Incidence

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In statistical epidemiology and health sciences, two essential metrics—prevalence and incidence—are fundamental for understanding disease dynamics within a population. These measures enable public health officials, epidemiologists, and researchers to assess the burden of diseases, allocate resources effectively, and design impactful public health policies and interventions.
Prevalence indicates the proportion of individuals in a population who have a specific disease or health...
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Overview
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Titrimetric Methods: Types and Commonly Used Strategies01:08

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In chemistry, titrimetric methods are broadly classified into three types: volumetric, gravimetric, and coulometric. Volumetric titrations involve measuring the volume of a titrant of known concentration that is required to react completely with an analyte. In gravimetric titrations, the standard solution reacts with the analyte to form an insoluble precipitate, which is filtered, dried, and weighed. In coulometric titrations, current is applied to an electrochemical reaction until the reaction...
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Compared with pure water, the solubility of an ionic compound is less in aqueous solutions containing a common ion (one also produced by dissolution of the ionic compound). This is an example of a phenomenon known as the common ion effect, which is a consequence of the law of mass action that may be explained using Le Châtelier’s principle. Consider the dissolution of silver iodide:
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Measures of species biodiversity, such as richness (i.e., the number of species present) and evenness (i.e., their relative abundance), describe an ecological community’s structure. Many factors affect community structure, including abiotic factors (e.g., sunlight and nutrients), disturbances (e.g., fire or flood), species interactions (e.g., predation or competition), and chance events (e.g., foreign species invasion). Certain species—such as keystone species—also play a...
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Speciation describes the formation of one or more new species from one or sometimes multiple original species. The resulting species are discrete from the parent species, and barriers to reproduction will typically exist. There are two primary mechanisms, speciation with and without geographic isolation—allopatric and sympatric speciation, respectively.
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Sampling for Estimating Frankliniella Species Flower Thrips and Orius Species Predators in Field Experiments
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通过无监督方法估计物种的常见性和流行率.

Pasquale Bove1, Andrea Bertini2, Gianpaolo Coro3

  • 1Istituto di Geoscienze e Georisorse, Consiglio Nazionale delle Ricerche, 56124, Pisa, Italy.

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概括

本研究引入了一种无监督的数据驱动方法,用于估计生态利基模型 (ENM) 的物种流行率. 该方法准确地分类了物种的常见性,提高了ENM对生物多样性研究的可靠性.

关键词:
人工智能的人工智能是人工智能.深度学习是一种深度学习.种类的共同性.种类的流行率 种类的流行率湿地 湿地 湿地

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科学领域:

  • 生态生态学 生态生态学
  • 生物多样性信息学 生物多样性信息学
  • 计算生物学 计算生物学

背景情况:

  • 物种流行对于生态利基模型 (ENM) 至关重要,但由于数据限制,特别是对于稀有物种,估计是具有挑战性的.
  • 准确的流行数据对于了解物种分布和环境关联至关重要.

研究的目的:

  • 开发和验证一个数据驱动的,无监督的方法来估计ENMs的物种流行率.
  • 提供对物种的客观和可靠的流行估计,特别是那些出现数据有限的物种.

主要方法:

  • 利用全球生物多样性信息设施记录多种多样性,无监督的方法.
  • 利用聚类方法,深度学习模型和对物种常见性分类的集体建模.
  • 将分类转化为流行概率,并根据专家评估进行评估.

主要成果:

  • 拟议的方法成功地分类了Massaciuccoli湖盆地的161种物种的物种流行率.
  • 所有模型都表现出高精度,其中深度学习模型的精度最高 (81-90%).
  • 这种方法被证明是可扩展的,可重复的,并且有效地产生可靠的流行率估计.

结论:

  • 开发的方法提供了一个可扩展和可重复的解决方案,用于估计物种流行率,增强生态利基模型.
  • 这种数据驱动的方法提供了客观的流行概率,对于生物多样性保护和生态研究至关重要.
  • 这些发现支持使用计算方法来克服生态研究中的数据限制.