I'm folowing the proof of corollary 1.8 page 5 of [Mörters - Sample path properties of Brownian motion](https://www.math-berlin.de/images/stories/lecnotes_moerters.pdf).

I want to show that $$\forall x,y \in \mathbb{R}^d , P_x\{y\in B\mathopen]0,1]\}=0$$ where $B$ is a $d$-dimensional Brownian motion.<br>
We will use the Lévy's theorem that says: $$\mathcal{L}_2(B[0,1])=0 \hspace{0.5cm} \text{almost surely.}$$

* in the first step we will show that $$\forall y \in \mathbb{R}^d,  P_x\{y\in B[0,1]\}=0  \hspace{0.5cm} \text{for $\mathcal{L}_2$-almost every } x \in \mathbb{R}^d$$
for any fixed $y\in\mathbb{R}^d$\begin{eqnarray*}
        \int_{\mathbb{R}^2}P_{y}(x\in B[0,1])dx&=&\int_{\mathbb{R}^2}\int_\Omega 1_{\{x\in B[0,1]\}}(\omega)dP_y(\omega)dx\\&=&\int_{\mathbb{R}^2}\int_\Omega 1_{B[0,1](\omega)}(x)dP_y(\omega)dx\\&=&\int_\Omega \int_{\mathbb{R}^2}1_{B[0,1](\omega)}(x)dxdP_y(\omega)\hspace{0.5cm} \text{by Tonelli}\\&=&
        \int_\Omega \mathcal{L}_2(B[0,1](\omega))dP_y(\omega)\\&=&
        E_{y}(\mathcal{L}_{2}(B[0,1])=0\\
    \end{eqnarray*}
so $$P_x\{y\in B[0,1]\}=0  \hspace{0.5cm} \text{for almost every } x \in \mathbb{R}^d$$
(now how can we get rid of the "for almost every $x$"?).
* in the second step he shows by symmetry of Brownian motion that: (but I don't know where did he use it) \begin{eqnarray*}
        P_{x}(y\in B[0,1])&=&P_{0}(y-x\in B[0,1])\\&=&P_{0}(y-x \in -B[0,1])\\&=&P_{y}(x\in B[0,1])=0\\
    \end{eqnarray*}
* in the third and last step he will get rid of the "for almost every $x$":
we will show that $\forall \epsilon >0, $ we have almost surely $P_{B(\epsilon)}\{y\in B[0,1]\}=0$ and we will find the result by sending $\epsilon$ to zero
  \begin{eqnarray*}
        P_{x}\{y\in B\mathopen]0,1]\}&=&P_{x}\{y=B_t / t\in \mathopen]0,1]\}
        \\&=&P_{x}(\bigcup_{\epsilon>0}\{ y=B_t / t\in \mathopen]\epsilon,1]\})\\&=& \lim_{\epsilon\rightarrow 0}P_{x}\{ y=B_t / t\in ]\epsilon,1]\}
        \\&=& \lim_{\epsilon\rightarrow 0}P_{x}\{ y=B_{t+\epsilon} / t\in \mathopen]0,1-\epsilon]\}
        \\&=& \lim_{\epsilon\rightarrow 0}P_{x}\{ y=B_{t+\epsilon}-B_\epsilon +B_\epsilon / t\in \mathopen]0,1-\epsilon]\}\\&=&
        \lim_{\epsilon\rightarrow 0}P_{x}\{ y=B_t+B_\epsilon / t\in \mathopen]0,1-\epsilon]\}\\&=&
         \underset{\epsilon \rightarrow 0}{\lim}P_{B\epsilon}\{ y=B_t+x / t\in \mathopen]0,1-\epsilon]\}\\&=&
         \underset{\epsilon \rightarrow 0}{\lim}\int_\Omega 1_{\{y=B_t+x / t\in \mathopen]0,1-\epsilon]\}}(\omega)dP_{B(\epsilon)}(\omega)\\&=&
\lim_{\epsilon\rightarrow 0} E_xP_{B(\epsilon)}\{y\in B[0,1]\}.
    \end{eqnarray*}
 
  I didn't get how he arrived to the last equation: $\lim_{\epsilon \rightarrow 0}\int_\Omega 1_{\{y=B_t+x / t\in \mathopen]0,1-\epsilon]\}}(\omega)dP_{B(\epsilon)}(\omega)=
\lim_{\epsilon\rightarrow 0} E_xP_{B(\epsilon)}\{y\in B[0,1]\}$.