The answer is C)4 for the <span>maximum number of covalent bonds a carbon atom can form with other atoms.</span>
Answer:
Independent variable: Salinity/Salt concentration
Dependent variable: hatching rate
Explanation:
As rightly stated in this question, INDEPENDENT VARIABLE, in an experiment, is the variable that the experimenter changes or manipulates in order to bring about a measurable response while the DEPENDENT VARIABLE is the variable that the experimenter measures in an experiment. Dependent variable as the name implies is dependent on the independent variable.
In this question where an hypothesis was given as follows: "Hatching brine shrimp is related to salinity (how salty the water is), then the greater the salt concentration, the higher the hatching rate". The hypothesis relates the independent and dependent variables i.e. it tells us how the independent variable affects the dependent variable.
Hence, according to the hypothesis, it is telling us how a change in SALINITY OR SALT CONCENTRATION will affect HATCHING RATE. Therefore;
Independent variable: SALINITY/SALT CONCENTRATION
Dependent variable: HATCHING RATE
Answer:
Cytoskeleton is the lattice-like structure of microtubules that support the cytoplasm and anchors organelles and also function in cytoplasmic streaming during cell crawling.
Explanation:
A group or network of protein fibers found within the cytoplasm is known as the cytoskeleton. It provides structural support for cells and is responsible for cell movement, cell stability, cell reproduction, cytoplasmic streaming or transportation of substances, etc. The movement of the cytoplasm within a plant or animal cell which helps to transport nutrients, proteins, and organelles within the cells is known as cytoplasmic streaming or protoplasmic streaming. The main three different types of protein-based filaments found in the cytoskeleton are microtubules, intermediate filaments, and microfilaments.
They are small, thick tubes made up of a protein called tubulin. They help to maintain cell shape and structure and are a part of the mitotic spindle which pulls homologous chromosomes apart during the cell division. The structures involved in cell movements such as cilia and flagella are also made up of microtubules. They help to resist the compression of the cell, provide pathways for secretory vesicles to move through the cell and also have a role in positioning the organelles within the cell.
They are thin filaments made up of a strong and flexible protein called actin. Actin filaments along with the protein myosin are responsible for cell movement and muscle contraction. Both proteins also have a role in splitting of a parent cell into daughter cells during cell division.
Their thickness is intermediate between the microfilaments (thinnest structure) and microtubules (thickest structure). They are made up of a protein called keratin and provide structure to the nuclear envelope and help anchor organelles together within a cell. Intermediate filaments along with the microtubules help to maintain cell shape and structure. They help to resist the tension of the cells and also link cells to other cells.
Answer:
Your answer should be Parasitism.
Example:
A flea on a dog: The flea benefits by getting shelter, and the food it needs to survive, the dog is harmed by getting its blood taken and getting infections.
Dependent and independent variables are variables in mathematical modeling, statistical modeling and experimental sciences. Dependent variables receive this name because, in an experiment, their values are studied under the supposition or hypothesis that they depend, by some law or rule (e.g., by a mathematical function), on the values of other variables. Independent variables, in turn, are not seen as depending on any other variable in the scope of the experiment in question; thus, even if the existing dependency is invertible (e.g., by finding the inverse function when it exists), the nomenclature is kept if the inverse dependency is not the object of study in the experiment. In this sense, some common independent variables are time, space, density, mass, fluid flow rate[1][2], and previous values of some observed value of interest (e.g. human population size) to predict future values (the dependent variable).[3]
Of the two, it is always the dependent variable whose variation is being studied, by altering inputs, also known as regressors in a statistical context. In an experiment, any variable that the experimenter manipulates[clarification needed] can be called an independent variable. Models and experiments test the effects that the independent variables have on the dependent variables. Sometimes, even if their influence is not of direct interest, independent variables may be included for other reasons, such as to account for their potential confounding effect.
