It is absolutely true to state that the role of an individual personality traits makes them more adaptable and comfortable to certain jobs. Selecting a career on the basis of your personality feature can result in a pleasant outcome. For example, if an individual is introvert, and if he chooses to become an anchor, just because it has a greater scope, tell me, can he thrive in this profession for a longer period of time?
Whenever, we hear such term in our day-to-day life, the first things that comes to our mind is of famous personalities, like Virat Kohli; Sachin Tendulker or Narendra Modi, etc. Not only this, we inspire from them and try to become like them, and in this process, we might lose our uniqueness. However, we never try to understand that what does personality actually mean?
We observed that generally the embedding representation is very rich and information dense. For example, reducing the dimensionality of the inputs using SVD or PCA, even by 10%, generally results in worse downstream performance on specific tasks.
Guided by the risk information-seeking and processing model, this study examines positive and negative affect separately in their influence on information-seeking intentions and avoidance through structural equation analyses. The highlight is that information avoidance seems to be driven by positive affect, while information seeking seems to be more heavily influenced by negative affect. Another interesting finding is that informational subjective norms are positively related to both seeking and avoidance, which suggests that one’s social environment has the potential to strongly influence the way he or she handles climate change information. Implications for theory and practice are discussed.
DNABERT: pre-trained Bidirectional Encoder Representations from Transformers model for DNA-language in genome - GitHub - jerryji1993/DNABERT: DNABERT: pre-trained Bidirectional Encoder Representations from Transformers model for DNA-language in genome
/**
* Called when a null model is about to be retrieved in order to allow a subclass to provide an
* initial model.
* <p>
* By default this implementation looks components in the parent chain owning a
* {@link IComponentInheritedModel} to provide a model for this component via
* {@link IComponentInheritedModel#wrapOnInheritance(Component)}.
* <p>
* For example a {@link FormComponent} has the opportunity to instantiate a model on the fly
* using its {@code id} and the containing {@link Form}'s model, if the form holds a
* {@link CompoundPropertyModel}.
*
* @return The model
*/
protected IModel<?> initModel()
{
IModel<?> foundModel = null;
// Search parents for IComponentInheritedModel (i.e. CompoundPropertyModel)
for (Component current = getParent(); current != null; current = current.getParent())
{
// Get model
// Don't call the getModel() that could initialize many in between
// completely useless models.
// IModel model = current.getDefaultModel();
IModel<?> model = current.getModelImpl();
if (model instanceof IWrapModel && !(model instanceof IComponentInheritedModel))
{
model = ((IWrapModel<?>)model).getWrappedModel();
}
if (model instanceof IComponentInheritedModel)
{
// return the shared inherited
foundModel = ((IComponentInheritedModel<?>)model).wrapOnInheritance(this);
setFlag(FLAG_INHERITABLE_MODEL, true);
break;
}
}
// No model for this component!
return foundModel;
}
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The impasse in math and science instruction runs deeper than test scores or the latest educational theory. What can we learn from the best teachers on the front