In characteristic $p$, the exact sequence $1\to K_s^{\times }\stackrel{p}{\to }{K}_s^{\times }\to K_s^{\times }/(K_s^{\times }{)}^p\to 1$ has a quotient killed by $p$. The characteristic p Galois dimension bound makes its second cohomology zero. Hence multiplication by $p$ on $\mathrm{Br}(K)$ is surjective. The root map is injective, and its failure of surjectivity on a separable closure is encoded by the quotient.

For $h\in L_0^2(P)$, truncate $h$ to $h_m=\max (-m,\min (h,m))$ and subtract $P{h}_m$. Dominated convergence gives $h_m\to h$ in L2 space, and the Cauchy-Schwarz inequality gives $P{h}_m\to 0$. Thus bounded centered directions are dense in the mean-zero L2 space. The measure defining the L2 norm is essential: density-weighted L2 space can contain functions outside the unweighted Lebesgue space.

For $0<x<y$, let $D_t=g_t(y)-g_t(x)$. Before the first boundary-point swallowing time for a Loewner chain, the ratio obeysThe clock $u=\int D_t^{-2}dt$ removes the denominator. An increasing scale function of a one-dimensional diffusion is $s_{\kappa }(z)={\int }_1^z[v(v-1){]}^{-4/\kappa }dv$. For $\kappa >4$ the endpoint $1$ represents strict swallowing; escape at infinite clock represents simultaneous swallowing.

A block design assigns treatments to experimental units partitioned into blocks. Its incidence counts $n_{ij}$ record how often treatment $i$ occurs in block $j$. Balance and connectedness determine which treatment contrasts are estimable and how much adjustment for blocks costs.

For independent Bernoulli observations with success probability $p$, the sample proportion is the success count divided by the sample size. It is an unbiased estimator with variance $p(1-p)/n$. It supplies the arm-specific risks in a risk ratio and the mean difference in a two-proportion comparison.

For $W\sim \mathrm{Bin}(n,p)$, expand the fourth power of the sum of centered independent Bernoulli variables. Terms with an index occurring once vanish; single-index fourth moments contribute $nq(1-3q)$ and paired second moments contribute $3n(n-1)q^2$. Their sum is the displayed formula. Scaling by $n^4$ yields a uniform $O(n^{-2})$ fourth moment for $W/n-p$.

Meta-regression relates study effect estimates to study-level explanatory variables. A common random-effects meta-analysis extension is $y_i=\alpha +\beta x_i+u_i+{\epsilon }_i$, where $\mathrm{Var}(u_i)={\tau }^2$ and $\mathrm{Var}({\epsilon }_i)=v_i$. For log odds ratios, $e^{\beta }$ is a ratio of underlying odds ratios per unit of $x$. Few studies, correlated design changes and exploratory variable selection limit interpretation; a study-level association does not identify an individual-level causal effect. The interpretation of study-level predictors is also discussed in the Cochrane methods handbook, section 10.11.

For ${\ell }_i={\lambda }_i+m-i$, the hook lengths in row $i$ are ${\ell }_i-q$, where $q$ runs over the non-beta numbers in $[0,{\ell }_i-1]$. Their product is ${\ell }_i!/{\prod }_{k>i}({\ell }_i-{\ell }_k)$. Multiplying over rows proves the identity and converts the hook-length formula into a Vandermonde determinant divided by factorials. Padding the partition with zero rows changes the beta set but not the hook product.

For a three-dimensional Bessel process started at one, $R$ stays strictly positive and satisfies $dR=dW+R^{-1}dt$. The Itô formula makes its reciprocal a local martingale, but $\mathbb{E}[R_t^{-1}]=2\Phi (1/\sqrt{t})-1<1$ for $t>0$. Thus the reciprocal is a strict local martingale. It can deflate the market with constant bank account and stock price $R$ without yielding a true pricing density for the bank account.

For a positive random variable $X$, write its base-ten logarithm as an integer part plus a fractional part:The floor function handles values below one as well: for $X=0.0042$, $K=-3$ and the decimal significand is $10^Z=4.2$. Since $10^Z\in [1,10)$, the first nonzero decimal digit is $D=\lfloor 10^Z\rfloor$. The monotonicity of the logarithm gives the exact event equivalenceIf $Z$ has the uniform distribution on $[0,1)$, the probability of this interval is its length. Consequently $\mathbb{P}(D=d)={\log }_{10}(d+1)-{\log }_{10}d$, proving the Benford law. This argument assumes uniformity of the fractional part of the logarithm, rather than uniformity of $X$ itself. See the logarithmic-coordinate explanation in Peter Sheridan Dodds, Benford's Law, essential story.

An exact constructed example is the log-uniform distribution on $[1,10)$, with probability density function $f_X(x)=1/(x\ln 10)$ there and zero elsewhere. Its total mass is ${\int }_1^{10}dx/(x\ln 10)=1$. The change of variables formula with $x=10^z$ gives $f_Z(z)=f_X(10^z)(\ln 10)10^z=1$ for $0\le z<1$. Equivalently, integrating directly givesFor example, the probability of first digit four is ${\log }_{10}(5/4)\approx 0.096910013$. By contrast, an ordinary uniform distribution for $X$ on $[1,10)$ has probability density function $1/9$ there, so $\mathbb{P}(D=d)={\int }_d^{d+1}dx/9=1/9$ for every digit. This is a concrete counterexample to any claim that the Benford law holds for every positive random variable.

More generally, a log-uniform distribution on $[A,B)$ with $0<A<B$ has uniform $Y={\log }_{10}X$ on $[{\log }_{10}A,{\log }_{10}B)$. If its logarithmic span ${\log }_{10}(B/A)=m$ is a positive integer, reduction to the fractional part wraps an interval of length $m$ around the unit interval exactly $m$ times, making $Z$ uniform even when $A$ is not a power of ten. Arbitrary partial-decade truncations generally do not have this property: for a log-uniform distribution on $[1,2)$, the first digit is always one.

Under the uniform fractional-logarithm assumption, multiplication by any constant $c>0$ replaces $Z$ by $Z^{\prime }=\{Z+{\log }_{10}c\}$. This is a rotation modulo one, which preserves the uniform distribution and therefore preserves the Benford law; see scale invariance of decimal significands. For the constructed $[1,10)$ example, multiplying by $0.001$ gives a log-uniform distribution on $[0.001,0.01)$ with the same digit probabilities. The claim concerns the decimal significand law: there is no proper probability density function proportional to $1/x$ over all of $(0,\infty )$, since its integral diverges. The existing scale-invariant prior describes that unnormalizable measure, while a finite log-uniform distribution is normalizable.

A decimal significand lies in $[1,10)$, obtained by removing the integer power of ten from a positive number. Multiplication by a constant rotates the fractional logarithm modulo one. Invariance under every such rotation makes the fractional logarithm uniform and hence implies Benford law. This is an invariant significand distribution, not a proper scale-invariant distribution for the entire positive number.

For a real vector $x$ with support of a vector $S$, this certificate is a vector $h$ whose measurements under the adjoint operator match the active sign function values and lie strictly between minus one and one on the inactive coordinates. If $A_S$ is injective, such a certificate proves that $x$ is the unique basis pursuit minimizer. For a nonzero $v\in \ker A$, injectivity ensures $v_{S^c}\ne 0$, and $0=⟨A^{\ast }h,v⟩$ implies the fixed-sign null space condition. The strict inequality is interpreted coordinatewise if $S^c$ is empty. The condition with the sign function written here is for real variables; complex basis pursuit uses the unit phases of active coordinates instead.

A parabolic Kepler orbit obeys $t=\sqrt{2q^3/(GM)}(D+D^3/3)$ with $D=\tan (f/2)$. At the high-eccentricity angular-speed crossover, $q\ll r_x$, so $n_p{t}_x\simeq (\sqrt{2}/3)(r_x/a_p{)}^{3/2}=2^{7/8}(q/a_p{)}^{3/8}/3$. The small time fraction explains why an eccentric orbit turns through almost $\pi$ of true anomaly while a distant perturber barely moves.

For the planar porous medium equation $n_t=[D_0/(3n_0^2)]\Delta (n^3)$, the mass-$Q$ point-source similarity solution is $n=n_0{\lambda }^{-2}\sqrt{[1-r^2/(r_0^2{\lambda }^2){]}_{+}}$, with $\lambda =(6D_{0}t/r_0^2{)}^{1/6}$ and $r_0^2=3Q/(2\pi n_0)$. Its front grows as $t^{1/6}$ and its central density falls as $t^{-1/3}$. The mass conservation integral uses the planar area element $2\pi rdr$. Although the density slope diverges at the front, its diffusion flux vanishes there, giving a compactly supported weak solution with initial measure $Q{\delta }^{(2)}$.

Reinvest each maturity payment in the next unit-principal zero-coupon bond. Positive bond prices make the resulting self-financing portfolio strictly positive, so it can be used as a numéraire. Its one-step growth is the reciprocal of the current one-period bond price.

A set containing a countable intersection of open dense subsets. The intersection itself is also called a residual set. In a Baire space it is dense. This topological notion of genericity does not by itself assert full measure.

In steady axisymmetric ideal magnetohydrodynamics, induction makes $\omega$ constant on regular connected poloidal flux surfaces. It describes field-line rotation. The material angular velocity is $u_{\varphi }/R=\omega +k{B}_{\varphi }/(\rho R)$ and differs when the toroidal magnetic field contributes. If the poloidal magnetic field vanishes, the flux-surface integration requires separate treatment.

For a pressure-free flowing poloidal flux surface, subtracting its angular velocity times the azimuthal momentum equation from the mechanical energy equation shows that ${ϵ}_J$ is constant. It equals poloidal kinetic energy plus $(u_{\varphi }-R\omega {)}^2/2+\Phi -R^2{\omega }^2/2$. This is the total magnetohydrodynamic Bernoulli invariant minus $\omega$ times the total magnetohydrodynamic angular-momentum invariant, not the total energy alone.

The Poisson equation for Newtonian gravity givesFor $V>0$, nonnegative mass density away from the origin is equivalent to $q^2\ge 1/2$. Strict positivity requires $q^2>1/2$. This condition does not by itself guarantee a nonnegative galactic distribution function.

Under ${\gamma }_{\mu \nu }\mapsto e^{2\omega }{\gamma }_{\mu \nu }$, the quadratic kinetic density of a $p$-brane scales as $e^{(p-1)\omega }$ and its constant density scales as $e^{(p+1)\omega }$. At $p=1$ the first factor is one and the constant term in the auxiliary-metric brane action vanishes. The traced metric equation is then an identity, leaving a Weyl transformation freedom. For $p\ne 1$, the metric equation instead identifies the auxiliary and induced worldvolume metrics.