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相关概念视频

Avoidance Learning and Learned Helplessness01:14

Avoidance Learning and Learned Helplessness

2.5K
Avoidance learning and learned helplessness are critical concepts in understanding behavioral responses to negative stimuli.
Avoidance learning occurs when an organism learns that a specific behavior can prevent an unpleasant outcome. For example, a student who receives a bad grade may start studying harder to avoid future poor grades. This behavior persists even when the negative outcome is no longer present. Avoidance learning is powerful because it maintains behavior in the absence of the...
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Learning Disabilities01:25

Learning Disabilities

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Learning disabilities are cognitive disorders caused by neurological impairments that affect cognitive functions like language and reading, without indicating overall intellectual or developmental challenges. These disabilities differ from global intellectual or developmental disabilities as they are limited to distinct cognitive functions. Common learning disabilities include dysgraphia, dyslexia, and dyscalculia, each of which impacts unique aspects of learning.
Dyslexia
Dyslexia is a...
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Associative Learning01:27

Associative Learning

1.3K
Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
1.3K
Purposive Learning01:22

Purposive Learning

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E. C. Tolman emphasized the purposiveness of behavior — the idea that much of our behavior is goal-directed. For instance, employees who aim for a promotion work diligently to meet their targets. Tolman argued that when classical conditioning and operant conditioning occur, the organism acquires certain expectations. In classical conditioning, a child might fear a dog because they expect it to bite. In operant conditioning, a person might consistently work overtime because they expect a...
457
Observational Learning01:12

Observational Learning

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Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning...
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Introduction to Learning01:18

Introduction to Learning

1.0K
Learning is the process of acquiring knowledge or skills through practice or experience, leading to long-lasting behavioral changes. This acquisition occurs through interaction with the environment and requires practice or experience. For instance, mastering a skill such as surfing requires considerable practice and experience, highlighting the essential role of repeated interactions with the environment in learning.
In contrast to learned behaviors, unlearned behaviors such as crying, sexual...
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相关实验视频

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Constructing and Visualizing Models using Mime-based Machine-learning Framework
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比较机器学习和深度学习框架,用于可靠的致癌性预测和活动悬崖分析.

Arkaprava Banerjee1, Vinay Kumar1, Kunal Roy1

  • 1Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata 700 032, India. kunal.roy@jadavpuruniversity.in.

Environmental science. Processes & impacts
|January 23, 2026
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概括

在老鼠中预测化学致癌性可以告知人类健康风险. 这项研究开发了先进的模型,发现使用ARKA描述符和人工神经网络的物流回归显示了致癌性的高预测能力.

科学领域:

  • 毒理学 毒理学 毒理学
  • 计算化学计算化学
  • 生物信息学是一种生物信息学.

背景情况:

  • 由于致癌性,工业化学品对人类健康构成风险.
  • 致癌性的预测模型对于风险评估至关重要.
  • 鼠类致癌性数据作为人类相关性的有价值的代理.

研究的目的:

  • 开发可靠的预测模型,用于小鼠的二进制致癌性数据.
  • 为了将大鼠的致癌性与人类的致癌性联系起来.
  • 为了确定影响化学致癌性的结构特征.

主要方法:

  • 采用了基于特征和化学语言建模方法.
  • 使用机器学习算法,包括人工神经网络 (ANN),开发了分类跨读结构-活动关系 (c-RASAR) 模型.
  • 基于SMILES字符串的模型使用了长短期内存 (LSTM) 架构,并使用了ARKA描述符的逻辑回归.

主要成果:

  • 后勤回归RASAR-ARKA模型表现出最好的性能.
  • 该ANN c-RASAR模型还显示了对外部数据的高效预测能力.
  • 该ARKA框架促进了活动悬崖的识别,并解释了预测错误.

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A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data
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A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data
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结论:

  • 开发的模型为预测化学致癌性提供了一个有效的框架.
  • 结构功能分析显示,原子 (氨酸衍生物,尼托胺) 和分支会增加致癌性.
  • 发现增加的分子尺寸可以降低致癌效应.