The carbon cycle is carbon compound are inconverted onto the environment
Answer:
A) The pollen grains will be pure red.
Explanation:
Plants have alternation of generations, this means that there are two different stages in their life-cycle: a sexual haploid (n) phase and an asexual diploid phase (2n). These phases occur in different individuals, so there is an haploid plant called gametophyte that carries gametes and after fecundation, it will rise a diploid sporophyte (asexual).
In seed plants, the sporophyte is the plant that we normally see, and the gametophyte is reduced into an organ of the sporophyte. The male gametophyte is the pollen that is produced in the sporangium in anthers (parts of sporophyte). When a pollen grain fecundes a female gametophyte (egg), it will produce a diploid embryo or new sporophyte.
Therefore, if the researcher exposes pollen to both stains, these grain will stain red, because red stain identifies gametophyte tissue.
Answer:nothing
Explanation:even though a smaller object would have a great force, a larger ob will move the smaller object farther
<u>Answer</u>:
The two molecules generated by the Krebs cycle that pass their high-energy electrons to the electron transport are NADH and FADH2
<u>Explanation:</u>
The kreb's cycle gives NADH and also the another hydrogen carrier which is termed as FADH2. During the process of the electron transport chain, one NADH gives rise to electrons and also the hydrogen ions, which has enough potential energy that can convert and produce 3 ATP molecules. Again in the electron transport chain the NADH and the FADH2 undergoes oxidation and releases energy in the form of the ATP. The process of generation of the ATP in the electron transport chain(ETC) is also referred as the chemiosmotic phosphorolation.
Category of AI that attempts to emulate the way the human brain works neural network.
A neural network is a biological neural network made up of biological neurons or an artificial neural network used to solve artificial intelligence (AI) problems.
Artificial neural networks model biological neuron connections as weights between nodes. An excitatory link is represented by a positive weight, whereas an inhibitory connection is represented by a negative weight. Each input is given a weight before being added together.
These artificial networks can be applied to adaptive control, predictive modelling, and other tasks where a dataset can be utilised to train them.
To learn more about artificial intelligence, refer this link brainly.com/question/28448080
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