Effect of dispersion parameters on normal curve geometry:

• In a normal distribution, the standard deviation $\sigma$ governs the spread (dispersion) of data. Since the total area under the curve is fixed at $1$, increasing $\sigma$ while keeping $\mu$ constant spreads out the probabilities over a larger range, causing the peak height $\frac{1}{\sigma \sqrt{2\pi}}$ to decrease and the bell curve to become flatter and wider (platykurtic spread).
• Normal distributions are always strictly symmetrical (skewness $= 0$), regardless of $\sigma$.
• smaller standard deviation makes the distribution narrower and more peaked (leptokurtic).
• Standard deviation fundamentally controls the horizontal spread and vertical height.

Characteristics of Smith-Waterman local alignment algorithm:

• Traceback starts at the highest scoring cell anywhere in the matrix and terminates as soon as a cell with score 0 is encountered.
• The first row and column are initialized with zeros ($H_{i,0} = H_{0,j} = 0$).
• In local alignment, cells are constrained by $H_{i,j} = \max(0, \dots)$, meaning scores are strictly non-negative; a score cannot be negative.
• Whenever a calculated alignment score drops below zero, it is reset to 0.

Fundamental capabilities and limitations of computers:

• Versatility is a core characteristic; computers can execute diverse tasks from numerical calculations to multimedia processing.
• Accuracy is a hallmark trait; computer calculations are consistently precise and error-free unless incorrect data is input (GIGO).
• Diligence is a defining characteristic; computers never suffer from human fatigue, boredom, or loss of concentration.
• I.Q. (Intelligence Quotient) is NOT a characteristic of computers; a computer has zero native I.Q. and cannot take decisions without programmed instructions.