Answer:
c. the entire planet was resurfaced about 750 million years ago.
Explanation:
Most of the craters (around 85%) on Venus are in immaculate condition although they have been slightly decayed by volcanism.
The crust of Venus is not in continuous motion like Earth's. This leads to the heat being trapped in the mantle. The crust of Venus undergoes a cyclical process every 100 million years or so. At the end of this cycle there is subduction occurs i.e., one tectonic plate moving sideways and moves down. Subduction recycles the crust.
The above factors also indicate that the entire planet was resurfaced about 750 million years ago
Don't look now, but the question GIVES you the formula to use, and it GIVES you the numbers to plug into the formula.
The formula to use to find the distance covered by the sound is
<em>Speed = (distance) / (time)</em>
They also give you:
speed = 330 m/s
time = 0.40 second
Stuff the numbers into the formula:
330 m/s = (Distance) / (0.40 second)
Multiply each side by (0.40 second), and you get:
(330 m/s) / (0.4 second) = Distance
<em>825 meters = Distance</em>
Answer:
average emf induced in the coil is 1.57 x V
Explanation:
Given data
n = 10 turns per centimeter = 1000 m^-1
N = 5
cross-sectional area A = 5.0 cm2 = 5.0 x 10^-4 m²
current = 0.25 A
to find out
average emf induced in the coil
solution
we will find emf by the given formula
emf = - (μ×N×n×A×ΔI ) / t ..................1
here
μ = 4π x 10^-7 and
N = 10
n = 1000
A = 5.0 x 10^-4
ΔI = 0.25
t = 0.050
put all value in equation 1
emf = - (μ×N×n×A×ΔI ) / t
emf = - (4π x 10^-7 ×5 ×1000× 5.0 x 10^-4 × 0.25 ) / 0.050
emf = 1.57 x V
average emf induced in the coil is 1.57 x V
Answer:
The description of the frame of reference is characterized below.
Explanation:
- Accuracy, as well as regression coefficients, seem to be the new standard measures besides summing up the validity of the developed modeling techniques.
- Classification accuracy unfortunately due to the presuppositions established by professionals on data sources with such an equitable classification process on supervised learning mostly with completely skewed category apportionment