Certain flavors of food are not available in Canada because of the harsh climate of the Nation.
Explanation:
Canada possesses a harsh and cold climate where there is hard to grow a lot of food and thus most of it is imported from outside throughout the year as farming in a land like Canada is very hard and not as fruitful as it would be somewhere temperate.
Thus the Canadians have a small variety of homegrown species which do not make up for a very tasty cuisine. Rest everything has to be painstakingly and with hassle imported from outside for the use of the people in Canada.
The water cycle has no starting point. But, we'll begin in the oceans, since that is where most of Earth's water exists. The sun, which drives the water cycle, heats water in the oceans. Some of it evaporates<span> as vapor into the air. Ice and snow can </span>sublimate<span> directly into water vapor. Rising air currents take the vapor up into the </span>atmosphere<span>, along with water from </span>evapo-transpiration<span>, which is water transpired from plants and evaporated from the soil. The vapor rises into the air where cooler temperatures cause it to </span>condense<span> into clouds. Air currents move clouds around the globe, cloud particles collide, grow, and fall out of the sky as </span>precipitation<span>. Some precipitation falls as snow and can accumulate as </span>ice caps and glaciers<span>, which can store frozen water for thousands of years. Snow packs in warmer climates often thaw and melt when spring arrives, and the melted water flows overland as </span>snow melt<span>. Most precipitation falls back into the oceans or onto land, where, due to gravity, the precipitation flows over the ground as </span>surface runoff<span>. A portion of runoff enters rivers in valleys in the landscape, with </span>stream flow<span> moving water towards the oceans. Runoff, and groundwater seepage, accumulate and are </span>stored as freshwater<span> in lakes. Not all runoff flows into rivers, though. Much of it soaks into the ground as </span>infiltration<span>. Some water infiltrates deep into the ground and replenishes </span>aquifers<span> (saturated subsurface rock), which store huge amounts of freshwater for long periods of time. Some infiltration stays close to the land surface and can seep back into surface-water bodies (and the ocean) as </span>groundwater discharge<span>, and some ground water finds openings in the land surface and emerges as freshwater </span>springs<span>. Over time, though, all of this water keeps moving, some to reenter the ocean, where the water cycle "ends" ... oops - I mean, where it "begins." Hope this helped!!</span>
Answer:
Generalization
Explanation:
In the conditioning process, the concept of generalization refers to the fact that the conditioned stimulus evokes similar responses when there's a similar stimulus present (once the response has been conditioned).
This means that once the response has been conditioned and it occurs in presence of certain stimulus, when a similar stimulus to the one the response now reacts to, appears, it creates the same conditioned response.
In this case, the <u>stimulus used is the ringing of a bell</u> that <u>has now the effect on Rover of bringing Dakota his slippers.</u> However, <u>the church bell sound is pretty similar to the bell that Dakota uses</u> and therefore Rover has the <u>same conduct (of bringing the slippers) when the church bell sounds. </u>
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Thus, this is an example of generalization.
B) The murder of an on-duty police officer.
Learning takes place in a connectionist network through a process of <u>back propagation</u> in which an error signal is transmitted starting from the property units.
<u>Explanation</u>:
Back propagation is a set of rules used for learning about the artificial neural networks using gradient descent. The gradient of the error function is calculated with respect to the neural network's weights.
This algorithm can be efficiently used to calculate the derivatives. Connectionist networks helps in arranging the neurons into a network. This network defines the arrangement of neurons, transmission function of neuron and a learning rule.
In back propagation, the error signal is transmitted from the property units.
