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相关概念视频

Steps in the Modeling Process01:14

Steps in the Modeling Process

687
Albert Bandura's theory of observational learning identifies four critical processes: attention, retention, motor reproduction, and reinforcement or motivation.
Attention is the first necessary component for observational learning. It involves focusing on what the model is doing and saying. For example, if you decide to take a drawing class to enhance your skills, you need to pay close attention to the instructor's words and hand movements. The characteristics of the model significantly...
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Parallel Processing01:20

Parallel Processing

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The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...
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Information Processing Approach01:30

Information Processing Approach

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The information-processing theory of cognitive development centers on fundamental mental processes, including attention, memory, and problem-solving skills. Researchers in this field examine how cognitive abilities, such as working memory, evolve and influence children's overall development. Studies indicate that children with stronger working memory tend to excel in reading comprehension, math, and problem-solving compared to peers with less efficient memory skills. Low working memory is...
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Processes of Self-Presentation01:29

Processes of Self-Presentation

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Effective self-presentation is a central component of social interaction and identity construction. It relies on the dynamic processes of defining the situation and engaging in self-disclosure. These mechanisms help individuals navigate social context expectations and manage how others perceive them, fostering mutual understanding and relationship development.Defining the SituationSocial situations are shaped by collectively understood frames—a set of widely understood rules or...
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Isothermal Processes01:21

Isothermal Processes

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A thermodynamic process that occurs at constant temperature is called an isothermal process. Heat slowly flows into the system or out of the system to maintain thermal equilibrium. Processes involving phase changes like water evaporation into steam or freezing water into ice at a constant temperature are examples of Isothermal Processes.
An ideal gas can also undergo isothermal expansion or compression.
For example, consider 1 mole of an ideal gas inside an isolated cylinder at initial volume V...
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Work Done in an Adiabatic Process01:20

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Consider the adiabatic compression of an ideal gas in the cylinder of an automobile diesel engine. The gasoline vapor is injected into the cylinder of an automobile engine when the piston is in its expanded position. The temperature, pressure, and volume of the resulting gas-air mixture are 20 °C, 1.00 x 105 N/m2, and 240 cm3 , respectively. The mixture is then compressed adiabatically to a volume of 40 cm3. Note that, in the actual operation of an automobile engine, the compression is not...
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相关实验视频

Updated: Feb 11, 2026

Recurrent Herpetic Stromal Keratitis in Mice, a Model for Studying Human HSK
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模拟使用概率性子过程的反复自杀企图.

Darío C Larese1, Pablo M Olmos1, Antonio Artés1

  • 1Department of Signal Theory and Communications, Carlos III University, Madrid, Spain.

Spanish journal of psychiatry and mental health
|February 9, 2026
PubMed
概括
此摘要是机器生成的。

自杀企图的复发集群是暂时的,大多数重复尝试发生在一年内. 基于霍克斯的建模为预防自杀提供了动态的,个性化的风险预测.

关键词:
多次自杀企图发生个性化预测个性化预测一个概率函数的概率函数.风险评估 风险评估

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科学领域:

  • 计算精神病学是一种计算精神病学.
  • 在医疗保健中的数学建模.
  • 自杀学是一种自杀学.

背景情况:

  • 评估自杀企图复发风险至关重要,但具有挑战性.
  • 现有的模型通常缺乏使用常规临床数据的动态预测.
  • 预测分析在预防自杀的努力中未得到充分利用.

研究的目的:

  • 开发和评估一个纵向数学模型来预测自杀企图的复发.
  • 利用常规临床数据进行动态风险估计.
  • 为了确定自杀企图复发的时间风险概况.

主要方法:

  • 分析了来自MCOSUL队列的1,112名个人,至少随访5年.
  • 使用了通过最大概率和神经网络估计的霍克斯过程参数.
  • 应用高斯混合模型来识别时间风险概况.

主要成果:

  • 自杀企图的复发表现出时间聚类,61.1%在1个月内,几乎所有在12个月内.
  • 该模型捕获了自我激发的动态,产生了个性化的风险曲线.
  • 确定了五个不同的时间风险集群,从低风险到极端风险.

结论:

  • 自杀尝试的重复表明自我激发的时间行为.
  • 基于霍克斯的建模提供了动态的,随时间变化的风险估计.
  • 这种方法可以增强个性化的自杀预防策略.