A mixed spreadsheet reference fixes exactly one coordinate. $A2 fixes column A and lets the row follow the copy; B$1 fixes row 1 and lets the column follow the copy. Put $2,3,4$ in A2:A4 and $5,6,7$ in B1:D1. Store =$A2*B$1 in B2, then fill the rectangle B2:D4. The colon denotes the inclusive rectangular range between the named corner spreadsheet cells. Each spreadsheet formula reads its row's factor from column A and its column's factor from row 1, producing a multiplication table.

Copying from B2 to D4 moves two columns right and two rows down. The mixed spreadsheet references become $A4 and D$1, so D4 contains =$A4*D$1 and has value $4\cdot 7=28$. For comparison, under that same displacement A2 becomes C4, $A$2 remains $A$2, $A2 becomes $A4, and A$2 becomes C$2. These four cases express the independent choice for each coordinate. Microsoft's official table demonstrates the same four possibilities for a two-row, two-column copy. ^[ref]

The filled rows have values $(10,12,14)$, $(15,18,21)$, and $(20,24,28)$. The multiplication table works because the left factor moves only vertically and the top factor moves only horizontally. Without the anchors, copying =A2*B1 from B2 to D4 would give =C4*D3, reading interior results rather than the intended boundary inputs.

// Target: computer-science.bigb

An absolute spreadsheet reference, such as $F$1, fixes both coordinates when its spreadsheet formula is copied. In the spreadsheet tabular model, every copied total reads the same tax rate. Absolute addressing retains the spreadsheet cell reference, not the value: changing the input in F1 changes the computed totals even though the references remain $F$1.

A relative spreadsheet reference, such as A2, allows both coordinates to change when its spreadsheet formula is copied. From C2, A2 means two columns left, in the same row. Copy =A2*B2 from C2 to C4: the displacement is zero columns and two rows, so it becomes =A4*B4. The row number changes to retain the same positional relationship to the spreadsheet formula.

An interspike interval is the elapsed time between consecutive action potentials in a spike train. Its probability distribution and dependence on previous activity can reveal a neuronal refractory period even when the average firing rate is unchanged.

Seed germination is renewed plant embryo activity and growth. Many germination assays score completion as radicle emergence, before seedling establishment. Seed imbibition precedes that endpoint; swelling alone is insufficient.^[ref]

Water, molecular oxygen and suitable temperature support germination; light sensitivity depends on the species and seed state. Neither illumination nor one particular temperature is universally required. Seed dormancy connects germination timing to ecology by delaying seedling establishment.^[ref]

The distinction matters when comparing propagation experiments: a treatment that increases radicle emergence need not improve later seedling survival. Define the endpoint before comparing treatments, then measure the later outcome separately.

A young plant developing after germination. Early growth can use a seed food reserve before leaves support photosynthesis.^[ref]

A nutritive plant tissue distinct from the plant embryo; it may remain in the mature seed or be depleted during development.^[ref]

Stored material supporting early seedling growth, located in cotyledons, endosperm or other plant tissues depending on the plant.

The protective covering of a seed, formed from maternal plant tissues surrounding the developing plant embryo.

The young plant inside a seed; its cotyledons and radicle are parts of the plant embryo.

An authored manufacturer experiment used an Agilent 1260 Infinity Bio-inert Quaternary LC with Bio SEC-3 $300\mathring{\mathrm{A}}$ columns, $7.8\mathrm{mm}$ diameter and $150$ or $300\mathrm{mm}$ length. Four pump channels mixed water, sodium chloride, and two phosphate solutions into $20\mathrm{mmol}{\mathrm{L}}^{-1}$ phosphate at pH $7.0$, varying salt from $0.2$ to $0.6\mathrm{mol}{\mathrm{L}}^{-1}$. At $1.0\mathrm{mL}\mathrm{mi}{\mathrm{n}}^{-1}$ and $30{}^{\circ }\mathrm{C}$, the readouts were diode-array absorbance, differential refractive index, and scattering at $15^{\circ }$ and $90^{\circ }$. A supplied protein standard mixture calibrated retention; bovine serum albumin calibrated scattering constants and inter-detector delay. Increasing salt improved separation of two α-chymotrypsinogen A peaks; two $300\mathrm{mm}$ columns also resolved peaks that one column did not. At $0.5\mathrm{mol}{\mathrm{L}}^{-1}$ salt, the two scattering-derived estimates were about $26,100$ and $25,800\mathrm{g}\mathrm{mo}{\mathrm{l}}^{-1}$. The author inferred a possible size-changing conformation difference, rather than doubling of molar mass. The same poster shows delayed, tailing lysozyme peaks from unwanted interactions.^[ref]

The salt comparison and the independent mass readout constrain interpretation, but do not uniquely prove a particular protein structure. Salt can change protein folding, protein aggregation, and packing interactions together. In ideal SEC there is no adsorption; attraction from the hydrophobic effect or forces described by electrostatics can cause additional retention, tailing, and loss of recovered sample. Repulsion can instead reduce pore entry. A peak beyond $V_t$ contradicts the simple nonbinding model, rather than extending its size calibration.

Useful proposed controls compare a solvent blank, fresh calibration standards bracketing the sample, several injection amounts and volumes, and recovered sample quantity with injected quantity using an appropriately calibrated detector. Keep temperature and volumetric flow rate fixed while testing pH or ionic strength. Compare an independent mass readout before declaring an early peak an aggregate. Loss of an insoluble species during filtration, on-column association or dissociation, overloading, and broad unresolved peaks can all hide the original sample population. These are interpretation checks and limitations, not measurements invented for the figures.

A SEC detector response must be specified before interpreting a peak area. Ultraviolet absorbance depends on a species' response factor and concentration, as described by the Beer-Lambert law; differential refractive index detection depends on how the dissolved species changes refractive index. Equal amounts need not produce equal signal areas across unlike species.

Even a calibrated mass-proportional trace is not a chain-count probability distribution. In an original two-population example, equal recovered masses of chains with molar masses $20,000$ and $80,000\mathrm{g}\mathrm{mo}{\mathrm{l}}^{-1}$ contain four times as many chains in the lighter population. Thus equal signal areas, assuming equal response per unit mass, correspond to number fractions $4/5$ and $1/5$: their number-average molar mass is $32,000\mathrm{g}\mathrm{mo}{\mathrm{l}}^{-1}$, while their weight-average molar mass is $50,000\mathrm{g}\mathrm{mo}{\mathrm{l}}^{-1}$. Converting a continuous trace additionally requires response correction and the appropriate change of variables between elution and molar mass bins.

When $A$ is an invertible matrix, the factorization in block elimination has outer triangular factors with determinant one. Hence $\det M=\det A\det S$, without a symmetry assumption. For the original example under block matrix inverse, this gives $\det M=(2\cdot 3)(19/6)=19$. An invertible block $A$ therefore reduces the question of whether the full matrix is an invertible matrix to the smaller Schur complement; a singular $S$ makes $M$ a singular matrix.

Let $M=\left(\begin{array}{cc}A& B\\ B^T& D\end{array}\right)$ be a real symmetric matrix with $A$ a positive-definite matrix. Its quadratic form satisfies the completing the square identityFor each fixed vector $y$, the unique minimizing vector is $x=-A^{-1}By$, so the minimized value is $y^{T}Sy$. Also, $M$ is a positive-definite matrix exactly when $S$ is a positive-definite matrix, under the stated assumption on $A$.^[ref]

An original scalar example isHere $A=2$, $B=1$, $D=3$, and the Schur complement is $5/2$. Holding $x=0$ would give $3y^2$, but letting $x$ relax to $-y/2$ reduces the quadratic form to $(5/2)y^2$. At $y=2$ the respective values are $12$ and $10$. Eliminating a variable therefore changes the effective cost of the retained variable.

This interpretation supports quadratic optimization and the positive-definite symmetric matrix tests used in Cholesky decomposition. In a multivariate normal distribution, a covariance matrix also gives a conditional covariance through a Schur complement; the required probabilistic hypotheses are supplied by conditional multivariate normal distribution, rather than by the algebra alone.

A supersaturated solution has an ion product above the relevant solubility product. It can persist through metastability: nucleation must first create a sufficiently large new solid region. Added surfaces, impurities and mixing history can affect that barrier. Therefore a clear sample during a finite observation does not prove undersaturation, and visible cloudiness does not measure the ion product.

An explicit Runge-Kutta method has $a_{ij}=0$ whenever $j\ge i$. Its stage matrix is strictly lower triangular: compute each Runge-Kutta stage using already known slopes, starting with $Y_1=y_n$. In contrast, an implicit Runge-Kutta method requires solving coupled stage equations, whose existence is addressed by stage solvability of an implicit Runge-Kutta method.

A Runge-Kutta stage consists of a trial state $Y_i$ at the time node $t_n+c_{i}h$ and the corresponding vector field evaluation $k_i$. In the slope convention, $Y_i=y_n+h{\sum }_j{a}_{ij}{k}_j$. Stages belong to the construction of one Runge-Kutta method step; they need not have the same accuracy as its final output. Stage states can leave the physically allowed region even when the endpoint lies inside it, so $f$ must be defined at every stage used.

A point reflection about $c$ sends each point $x$ to $2c-x$. The point $c$ is the midpoint of $x$ and its image, and applying the map twice is the identity. It is a Euclidean isometry since $(2c-x)-(2c-y)=-(x-y)$ preserves the Euclidean norm. In the Euclidean plane it is a rotation through $\pi$; in dimension $n$ its determinant is $(-1{)}^n$, so it reverses orientation exactly in odd dimension. A figure invariant under this map has $c$ as a center of symmetry.