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相关概念视频

Social Exchange Theory02:06

Social Exchange Theory

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We have discussed why we form relationships, what attracts us to others, and different types of love. But what determines whether we are satisfied with and stay in a relationship? One theory that provides an explanation is social exchange theory. According to social exchange theory, we act as naïve economists in keeping a tally of the ratio of costs and benefits of forming and maintaining a relationship with others (Rusbult & Van Lange, 2003).
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Evolutionary Psychology01:20

Evolutionary Psychology

255
Evolutionary psychology explores the origins of human behavior and mental processes by framing them within the context of natural selection, a theory famously propounded by Charles Darwin. This field asserts that many behaviors common across human societies — ranging from instinctive fear reactions to complex social interactions — arose as evolutionary adaptations. These adaptations enhanced the survival and reproductive success of our ancestors, thereby becoming embedded in the...
255
Theories of Dissolution: Diffusion Layer Model01:15

Theories of Dissolution: Diffusion Layer Model

702
Dissolution, the process by which drug particles dissolve in a solvent, is explained by the diffusion layer model, a theoretical framework that simulates the absorption of oral drugs and allows us to analyze experimental data.
This process starts with a thin layer, saturated with the drug, forming at the interface between the solid and liquid. The solute then diffuses from this layer into the main solution. The Noyes-Whitney equation suggests that the rate of dissolution relies on the diffusion...
702
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

32
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
32
Relationship Formation02:12

Relationship Formation

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What do you think is the single most influential factor in determining with whom you become friends and whom you form romantic relationships? You might be surprised to learn that the answer is simple: the people with whom you have the most contact. This most important factor is proximity. You are more likely to be friends with people you have regular contact with. For example, there are decades of research that shows that you are more likely to become friends with people who live in your dorm,...
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Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

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Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
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相关实验视频

Updated: Jun 12, 2025

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
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Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

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在基于代理的模型中共同发展的意见和社会动态网络.

Nataša Djurdjevac Conrad1, Nhu Quang Vu1,2, Sören Nagel1

  • 1Zuse Institute Berlin, 14195 Berlin, Germany.

Chaos (Woodbury, N.Y.)
|September 17, 2024
PubMed
概括

数字社交媒体推动了论和社会互动的共同进化. 我们的模型显示了社会关系和观点如何动态地相互影响,影响集体结果和像回声室这样的现象.

科学领域:

  • 计算社会科学 计算社会科学
  • 网络科学 网络科学
  • 社会学 社会学 社会学

背景情况:

  • 数字社交媒体放大了公众意见和社会互动的共同演变.
  • 现有的研究往往将这种模式视为单向,从意见到社会关系.
  • 这忽视了社会动态对论形成的相互影响.

研究的目的:

  • 引入一种共同发展的意见和社会动态的模型.
  • 分析新出现的现象背后的机制,如回声室和共识.
  • 将模型应用于真实世界的数据以进行验证.

主要方法:

  • 基于随机代理的建模.
  • 代理人的流动性受到社会和意见相似性的影响.
  • 由社会邻近感驱动的意见形成.

主要成果:

  • 该模型捕捉了社会联系和意见演变之间的动态相互作用.
  • 对社会和意见网络的分析揭示了关键的交互机制.
  • 成功应用于关于政治身份的一般社会调查数据.

结论:

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  • 社会互动和观点动态地共同发展,影响社会结构.
  • 该模型为理解复杂的社会现象提供了一个框架.
  • 展示了基于代理的模型在社会科学研究中的实用性.