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相关概念视频

Mathematical Modeling: Problem Solving01:29

Mathematical Modeling: Problem Solving

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Mathematical modeling transforms real-world scenarios into mathematical expressions, allowing for structured problem-solving and analysis. This process involves defining the situation, assigning variables to measurable quantities, selecting an appropriate model, and solving the resulting equation. Such models are invaluable in finance, providing precise methods to evaluate investments, loans, and repayment structures.A widely used example is the calculation of fixed monthly payments on a loan,...
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Modeling with Differential Equations01:25

Modeling with Differential Equations

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Population dynamics can be described mathematically by considering the population size P(t) as a function of time. The rate of change of the population is then represented by the derivative of P(t). A simple assumption is that the rate of growth is proportional to the size of the population itself. This leads to an exponential growth model, where the population increases rapidly without bound. While this is a useful first approximation, it does not reflect realistic long-term...
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Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

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Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
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Quadratic Models01:23

Quadratic Models

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Quadratic models are mathematical representations used to describe relationships in which the rate of change changes at a constant rate. These models appear in a wide variety of natural and engineered systems, especially those involving motion, forces, and optimization. One common application is analyzing the vertical motion of objects influenced by gravity, such as a ball thrown into the air.In such scenarios, the object's height changes over time in a curved pattern, rising to a maximum point...
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Fundamental Mathematical Principles in Pharmacokinetics: Calculus and Graphs01:21

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The fundamental mathematical principles, such as calculus and graphs, play crucial roles in analyzing drug movement and determining pharmacokinetic parameters. Differential calculus examines rates of change and helps to determine the dissolution rate of drugs in biofluids, as well as how drug concentrations change over time. For instance, it can help calculate the rate of elimination of a drug from the body based on its concentration-time profile.
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Growth Models with Integration: Problem Solving01:27

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In population modeling, integration provides a systematic way to determine accumulated quantities from known rates of change. One such application arises in ecology, where the total weight of a fish population in a body of water is referred to as its biomass. When the rate of growth of this biomass is known as a function of time, calculus can be used to determine the total biomass at a future date.Growth Rate and Biomass FunctionLet the growth rate of the fish population be represented by a...
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Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
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数学建模的数学建模

Botond Szilágyi1

  • 1Budapest University of Technology and Economics, Budapest, Hungary. szilagyi.botond@vbk.bme.hu.

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|March 13, 2026
PubMed
概括
此摘要是机器生成的。

溶液结晶对于制药生物分子分离和净化至关重要. 数学建模和控制策略增强了对这些绿色,可扩展的工业过程的理解,设计和优化.

关键词:
生物分子结晶的过程结晶过程的设计设计.变态稳定的中间阶段.核和生长动力学的核和生长动力学.颗粒大小分布 颗粒大小分布人口平衡模型的人口平衡模型过程分析技术 过程分析技术解决性建模 解决性建模

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科学领域:

  • 生物化学和制药工程 生物化学和制药工程
  • 化学工程和工艺控制控制的过程.

背景情况:

  • 溶液结晶对于生物分子分离,净化和制药中的颗粒形成至关重要.
  • 它提供了一种绿色和可扩展的工业方法,尽管宏分子结晶可能具有挑战性.
  • 必须优化关键的热力学条件 (溶剂,沉剂,度,pH,温度).

研究的目的:

  • 提供结晶过程工程的概述,重点是数学建模和控制.
  • 将生物分子结晶的理解与已建立的无机结晶理论相结合.
  • 详细介绍工艺理解,设计,优化和工业规模控制的方法.

主要方法:

  • 数学建模和模拟用于过程分析和优化.
  • 为工业结晶器开发控制解决方案.
  • 利用生物分子系统的已建立的结晶理论.

主要成果:

  • 证明了数学建模的适用性,用于理解,分析和优化结晶过程.
  • 提出了控制策略,以便在结晶器中有效实现所需产品.
  • 突出了生物分子和无机小分子晶体生长机制之间的对应性.

结论:

  • 数学建模和控制是推动工业规模生物分子结晶的重要工具.
  • 生物分子结晶行为在很大程度上与无机结晶原理保持一致.
  • 这项工作为优化制药结晶过程提供了一个框架.