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If $f \sim g$ and $g \sim h$, then $f \sim h$.
If $a \sim_F b$ and $b \sim_F c$, then $a \sim_F c$.
If $f(a) \sim b$ and $a \sim c$, and $f$ is asymptotically equivalent, then $f(c) \sim b$.
If $f$ is asymptotically equivalent to the constant function $c$, then $f$ converges to $c$.
If two functions are eventually equal, then they are asymptotically equivalent.
If $f$ and $h$ are asymptotically equivalent and $f \leq g \leq h$, then $f$ and $g$ are asymptotically equivalent, and $g$ and $h$ are asymptotically equivalent.
If two functions are asymptotically equivalent, then they eventually have the same sign.
If two functions are asymptotically equivalent, then they eventually have the same sign, and eventually have the same sign when negative or positive.
If $f$ and $g$ are asymptotically equivalent and $f$ tends to $c$, then $g$ tends to $c$.
If two functions are asymptotically equivalent, then they have the same limit.
If $g(x)$ is $o(f(x))$, then eventually $sgn(f(x) + g(x)) = sgn(f(x))$.
If two measures agree on the sets $\{x < \cdot\}$ for all $x$, then they are equal.
If $F$ is a monotone function that is right-continuous, then the Lebesgue measure of the interval $[a,b]$ is $F(b) - F(a)$.
If $F$ is a continuous increasing function on the real line, then the Lebesgue measure of the interval $[a, b]$ is $F(b) - F(a)$.
If $F$ is a nondecreasing function and is continuous from the right, then the Lebesgue measure of the interval $(a,b)$ is $F(b) - F(a)$.
The sets of the interval measure $F$ are the same as the sets of the Borel measure.
The space of an interval measure is the entire universe.
If $F$ is a continuous, monotone function, then the Lebesgue measure of the interval $[a,b]$ is $F(b) - F(a)$.
If $F$ is a monotone right-continuous function, then the interval measure $\mu$ defined by $\mu(a,b] = F(b) - F(a)$ is a $\sigma$-finite measure.
If $P(x)$ holds almost everywhere on $S$, and $P(x)$ implies $Q(x)$ for all $x \in S$, then $Q(x)$ holds almost everywhere on $S$.
If $S$ is a null set, then the Lebesgue integral of $f$ over $S$ is zero.
The Lebesgue measure on the real line is the same as the Borel measure on the real line.
The space of the Lebesgue measure on a set $S$ is $S$.
The Lebesgue measure of a set is always a Lebesgue measurable set.
The complement of a Lebesgue measurable set is Lebesgue measurable.
If two functions agree on a set $S$, then they are Lebesgue measurable on $S$ if and only if they are Lebesgue measurable on $S$.
The Lebesgue measure on $\mathbb{R}$ is the same as the Lebesgue measure on $\mathbb{R}$ restricted to $\mathbb{R}$.
If $S$ and $T$ are measurable sets, then the integral of $f$ over $S \cap T$ is equal to the integral of $f$ over $T$ restricted to $S$.
If $S$ is a subset of $T$ and both $S$ and $T$ are Lebesgue measurable, then the integral of $f$ over $S$ is equal to the integral of $f$ over $T$ restricted to $S$.
If $f$ is a Lebesgue-integrable function on a set $S$, then the integral of $f$ over $S$ is equal to the integral of $f$ over the whole space, restricted to $S$.
The Lebesgue integral of any function over the empty set is zero.
The Lebesgue integral of a function over the empty set is zero.
If $f$ is a Bochner integrable function on a measurable space $M$, then $f$ is also Bochner integrable on the restriction of $M$ to any measurable subset $\Omega$.
If $f$ is a function defined on a Lebesgue measurable set $S$, then $f$ is Lebesgue integrable on $S$ if and only if the function $x \mapsto f(x)$ if $x \in S$ and $0$ otherwise is Lebesgue integrable on $\mathbb{R}^n$.
If $f$ is an integrable function on a set $T$ and $g$ is a function on a subset $S$ of $T$ such that $g(x) \leq f(x)$ for almost all $x \in S$, then $\int_S g \leq \int_T f$.
If $f$ is a Borel measurable function defined on a set $S$, then the function $g$ defined by $g(x) = f(x)$ if $x \in S$ and $g(x) = 0$ otherwise is also Borel measurable.
If $f$ is a Borel measurable function on $\mathbb{R}^n$, then $f$ is a Borel measurable function on any Borel subset of $\mathbb{R}^n$.
If $f$ is a Borel measurable function on a set $S$, then the function $g$ defined by $g(x) = f(x)$ if $x \in S$ and $g(x) = 0$ otherwise is a Borel measurable function on $\mathbb{R}^n$.
If $S$ and $T$ are Lebesgue measurable sets with $S \subseteq T$, then a function $f$ is Lebesgue measurable on $S$ if and only if the function $x \mapsto f(x)$ if $x \in S$ and $0$ otherwise is Lebesgue measurable on $T$.
A function $f$ is Lebesgue measurable if and only if for every $a \in \mathbb{R}$ and every $i \in \{1, \ldots, n\}$, the set $\{x \in S \mid f(x)_i < a\}$ is Lebesgue measurable.
A function $f$ is Borel measurable if and only if for all $a \in \mathbb{R}$ and $i \in \{1, \ldots, n\}$, the set $\{x \in S: f(x)_i \geq a\}$ is measurable.
A function $f$ is Borel measurable if and only if for all $a \in \mathbb{R}$ and $i \in \{1, \ldots, n\}$, the set $\{x \in S: f(x)_i > a\}$ is measurable.
A function $f$ is Borel measurable if and only if the preimage of every halfspace is a Borel set.
A function $f$ is Borel measurable if and only if the preimage of every open interval is a Lebesgue measurable set.
A function $f$ is Borel measurable if and only if the preimage of every closed set is a Lebesgue measurable set.
A function $f$ is Borel measurable if and only if the preimage of every closed interval is a Lebesgue measurable set.
A function $f$ is Lebesgue measurable if and only if the preimage of every Borel set is a Lebesgue measurable set.
If $f$ is a Lebesgue-measurable function and $T$ is a Borel set, then the preimage of $T$ under $f$ is a Lebesgue-measurable set.
A function $f$ is Lebesgue measurable if and only if the preimage of every Borel set is a Lebesgue measurable set.
If $f$ is a continuous function defined on a Lebesgue measurable set $S$, then $f$ is Lebesgue measurable on $S$.
The identity function is Lebesgue measurable.
The identity function is measurable with respect to the Lebesgue measure on $S$.
The Lebesgue measure on the real line is the same as the interval measure.
The Lebesgue measure on $\mathbb{R}^n$ is the product measure of the Lebesgue measure on $\mathbb{R}$ with itself $n$ times.
If $f_1, \ldots, f_n$ are nonnegative measurable functions on $\mathbb{R}$, then $\int_{\mathbb{R}^n} f_1(x_1) \cdots f_n(x_n) \, dx_1 \cdots dx_n = \int_{\mathbb{R}} f_1(x_1) \, dx_1 \cdots \int_{\mathbb{R}} f_n(x_n) \, dx_n$.
The Lebesgue measure of an interval $[l, u]$ is $u - l$.
The Lebesgue measure of the interval $[l, u]$ is $u - l$ if $l \<le> u$ and $0$ otherwise.
The Lebesgue measure of a box is the product of the lengths of its sides.
For any $c \in \mathbb{R}^n$, the set $\{c\}$ has Lebesgue measure zero.
The Lebesgue measure of the open interval $(l, u)$ is $u - l$.
The Lebesgue measure of an open interval is its length.
The Lebesgue measure of an interval is its length.
The Lebesgue measure of a box is the product of the lengths of its sides.
The Lebesgue measure of a box is the product of the lengths of its sides, if the box is nonempty, and zero otherwise.
The Lebesgue measure of a box is the product of the lengths of its sides, if the box is non-empty, and zero otherwise.
The Lebesgue measure of a singleton set is zero.
The Lebesgue measure of a closed interval is finite.
The Lebesgue measure of a box is finite.
The Lebesgue measure of a ball in $\mathbb{R}^n$ is finite.
The Lebesgue measure of a ball in $\mathbb{R}^n$ is finite.
The closed and open boxes are measurable.
The Lebesgue measure of an interval is its length.
If $l$ and $u$ are vectors in $\mathbb{R}^n$ such that $l \leq u$, then the Lebesgue measure of the box $[l, u]$ is $\prod_{i=1}^n (u_i - l_i)$.
The Lebesgue measure of a box is the product of the lengths of its sides if the box is nonempty, and zero otherwise.
The Lebesgue measure of a box is the product of the lengths of the sides of the box, if the box is nonempty, and zero otherwise.
The Lebesgue measure of a singleton set is zero.
The Lebesgue measure on the real line is sigma-finite.
The Lebesgue measure of the entire space is infinite.
If $A$ is a countable set, then the Lebesgue measure of $A$ is zero.
If $A$ is a countable set, then $A$ is a null set.
If $A$ is a finite set, then $A$ is a null set.
The set $N$ is a null set if and only if the set $N \cup \{a\}$ is a null set.
If $a$ is in $S$ and $S$ is a Lebesgue measurable set, then the set $N \cup \{a\}$ is a null set in the Lebesgue measure on $S$ if and only if $N$ is a null set in the Lebesgue measure on $S$.
The Lebesgue measure on $\mathbb{R}^n$ is not the counting measure on any set $A \subset \mathbb{R}^n$.
If $S$ is an open set, $C$ is a closed set, and almost every point of $S$ is in $C$, then $x \in S$ implies $x \in C$.
If $C$ is a closed set and almost every point of the real line is in $C$, then $x \in C$.
If the Lebesgue measure of a box is the product of the lengths of its sides, then the measure is the Lebesgue measure.
The Lebesgue measure on $\mathbb{R}^n$ is the pushforward of the Lebesgue measure on $\mathbb{R}$ under the map $T(x) = t + \sum_{j=1}^n c_j x_j$, where $c_j
The Lebesgue measure on $\mathbb{R}^n$ is the same as the measure obtained by translating the Lebesgue measure on $\mathbb{R}^n$ by $t$ and then scaling it by $c$.
The Lebesgue measure on the real line is the pushforward of the Lebesgue measure on the real line under the affine transformation $x \mapsto t + c x$.
If $P$ is a Borel-measurable predicate, then the set of $x$ such that $P(x)$ holds is almost everywhere equal to the set of $x$ such that $P(t + cx)$ holds.
If $f$ is a non-negative measurable function, then $\int f(x) dx = c \int f(t + cx) dx$ for any $c \neq 0$.
If $f$ is integrable, then so is $f(t + cx)$ for any $c \neq 0$.
If $f$ is a real-valued function defined on the real line, then $f$ is integrable if and only if $f(t + cx)$ is integrable for any $t, c \in \mathbb{R}$.
If $f$ is a real-valued function, then $\int f(x) dx = c \int f(t + cx) dx$ for any constant $c \neq 0$.
If $c$ is a vector of nonzero real numbers, then the Lebesgue measure of the set $T = \{t + \sum_{j \in \text{Basis}} c_j x_j \mid x \in \mathbb{R}^n\}$ is equal to the product of the absolute values of the $c_j$'s.
The Lebesgue measure on the real line is the pushforward of the Lebesgue measure on the real line under the affine transformation $x \mapsto t + c x$.
If $f$ is a measurable function on the real line, then $\int f(x) dx = c \int f(t + cx) dx$ for any $c \neq 0$.
The function $x \mapsto x \cdot y$ is Lebesgue measurable for any $y \in \mathbb{R}$.
The Lebesgue measure of an affine transformation of a set is equal to the absolute value of the determinant of the transformation times the Lebesgue measure of the set.