B. carry information from genes to ribosomes.
C. transfer amino acids to ribosomes.
D. make DNA.
Answer:
In his experiment, Griffith used two strains of Streptococcus pneumoniae type II- rough(R) strain and a type III smooth(S) strain. The type III smooth strain had an outer polysaccharide capsule which makes smooth strain a virulent strain.
So in his experiment, Griffith injected these strains in mice in an order and observed the result. When he
injected living S strain- Mice died
Injected living R- strain- Mice survived
Injected heat-killed S strain- Mice survived
Injected heat S strain+ living R strain- Mice died
So after his experiment, he concluded that R strain took something from heat killed S strain which transformed the R strain into virulent strain that killed the Mice. So based on this experiment Griffith gave transformation principle.
Answer:
Organisms
Explanation:
When we speak of geological time, we refer to a time scale that is usually measured in millions or even billions of years, such as the classification of geological ages and their respective periods. Geological time is a scale obtained from the relative dating of the rocks, either by observing the marks of the events recorded in them, either by the order of superposition of the sedimentary layers or by the fossils they contain, or even by the absolute dating of the rocks, through calculating the rate of disintegration of a radioactive isotope. Radiometric dating of rocks from the Moon and meteorites gave an approximate age of the planet Earth in 4.5 billion years. In addition, geological time is divided into units based on the types of organisms.
Geologic time is divided into units based upon types fossils found in each area .
I hope that's help !
b. List all the parameters you think might be relevant to this model. Describe in words the meaning of each parameter and any restrictions on their values.
c. Justify whether this should be a discrete time model or continuous time model.
a. State Variables and State Space:
1.Cell Density (N): The number of yeast or bacterial cells present in the chemostat at a given time. The state space for N is the set of non-negative real numbers (N ≥ 0).
2.Concentration of Substrate (S): The concentration of the nutrient (e.g., glucose) in the liquid medium. The state space for S is the set of non-negative real numbers (S ≥ 0).
3.Dilution Rate (D): The rate at which medium is added to the chemostat relative to the volume of the chemostat. The state space for D is the set of non-negative real numbers (D ≥ 0).
4.Effluent Concentration (S_out, N_out): The concentration of substrate and cell density in the effluent leaving the chemostat. The state space for S_out and N_out is the set of non-negative real numbers (S_out ≥ 0, N_out ≥ 0).
b. Parameters:
1.Maximum Specific Growth Rate (μ_max): The maximum growth rate of cells under ideal conditions (maximal nutrient availability and absence of inhibitory factors). It is a positive real number (μ_max > 0).
2.Half-Saturation Constant (K_s): The concentration of substrate at which the specific growth rate is half of μ_max. It is a positive real number (K_s > 0).
3.Yield Coefficient (Y): The amount of biomass (cells) produced per unit of substrate consumed. It is a positive real number (Y > 0).
4.Dilution Rate (D): This is both a state variable and a parameter. As a parameter, it represents the rate at which medium is added to the chemostat, and it can vary within the state space (D ≥ 0).
5.Inlet Concentration (S_in): The concentration of substrate in the incoming medium. It is a positive real number (S_in > 0).
6.Effluent Flow Rate (Q): The rate at which medium and cells exit the chemostat through the effluent tube. It is a positive real number (Q > 0).
7.Cell Death Rate (μ_death): The rate at which cells die in the chemostat due to factors such as predation or aging. It is a positive real number (μ_death > 0).
c. Justification for Model Type:
This should be a continuous time model because the growth and dynamics of yeast and bacterial populations in a chemostat occur continuously over time. Cells divide continuously, and changes in cell density, substrate concentration, and other state variables are continuous and smooth. Discrete time models, which operate in discrete time steps, may not capture the nuances of these continuous processes accurately. Therefore, a continuous time model, possibly using differential equations, would better represent the system's behavior in a chemostat.
It’s a sugar found in RNA but not in DNA