Answer:
Explanation:
= Velocity of car = 65 mph = 
= Density of air = 
From Bernoulli's law we have
The maximum pressure on the girl's hand is
Now = 200 mph = 
The maximum pressure on the girl's hand is
Answer:
Explanation:
Our values are,
State 1
We know moreover for the tables A-15 that
State 2
For tables we know at T=320K
We need to use the ideal gas equation to estimate the mass, so
Using now for the final mass:
We only need to apply a energy balance equation:
The negative value indidicates heat ransfer from the system
Answer: b)Its ability to penetrate skin quickly due to its very small diameter
Explanation: Carbon nano tubes(CNT) are the material widely used in the medical field due to the atomic structure of it ans also have small size. Toxicity in the carbon nano tubes is because their small sized atomic particles which can enter the skin by penetration or inhalation. But are still preferred in the medicine because having unique properties like mechanical property, chemical property,surface property etc.
Answer:
In ferrous metal iron present but on the other hand in the non ferrous material iron does not present.That is why there is a different heat treatment process for ferrous and nonferrous materials.
Ferrous materials contains iron is the main constitute.Like steel ,cast iron ,wrought iron .Steel and cast iron are the alloy element of iron ans carbon.Wrought iron is the purest from of iron.
Heat treatment process for ferrous materials :
1.Normalizing
2.Annealing
3.Quenching
4.Surface hardening
Heat treatment process for non ferrous materials :
Mostly annealing process is used for non ferrous materials.After annealing non ferrous will become soft.
When two metal plates are joined then they form a bimetallic structure.The bimetallic structure is used to find the relationship of thermal temperature and the mechanical displacement.
The use of bimetallic structure -In clock ,thermometers ,engines.
Features of Multidimensional scaling(MDS) from scratch is described below.
Explanation:
Multidimensional scaling (MDS) is a way to reduce the dimensionality of data to visualize it. We basically want to project our (likely highly dimensional) data into a lower dimensional space and preserve the distances between points.
If we have some highly complex data that we project into some lower N dimensions, we will assign each point from our data a coordinate in this lower dimensional space, and the idea is that these N dimensional coordinates are ordered based on their ability to capture variance in the data. Since we can only visualize things in 2D, this is why it is common to assess your MDS based on plotting the first and second dimension of the output.
If you look at the output of an MDS algorithm, which will be points in 2D or 3D space, the distances represent similarity. So very close points = very similar, and points farther away from one another = less similar.
Working of MDS
The input to the MDS algorithm is our proximity matrix. There are two kinds of classical MDS that we could use: Classical (metric) MDS is for data that has metric properties, like actual distances from a map or calculated from a vector
.Nonmetric MDS is for more ordinal data (such as human-provided similarity ratings) for which we can say a 1 is more similar than a 2, but there is no defined (metric) distance between the values of 1 and 2.
Uses
Multidimensional scaling (MDS) is a means of visualizing the level of similarity of individual cases of a dataset. MDS is used to translate "information about the pairwise 'distances' among a set of n objects or individuals" into a configuration of n points mapped into an abstract Cartesian space.
