diff --git a/articles/figures/fig_1.png b/articles/figures/fig_1.png
new file mode 100644
index 0000000..64aaba6
Binary files /dev/null and b/articles/figures/fig_1.png differ
diff --git a/articles/technical_details.html b/articles/technical_details.html
index 95bbb2b..a21a6d4 100644
--- a/articles/technical_details.html
+++ b/articles/technical_details.html
@@ -77,17 +77,17 @@
Technical details
-
-Figure 1: Left: One simulated dataset generated according to
-\(\mathcal{MN}_{100\times
-2}(\textbf{0}_{100\times 2}, \textbf{I}_{100}, \sigma^2
-\textbf{I}_{2})\). We apply \(k\)-means clustering to obtain three
-clusters. The cluster centroids are displayed as triangles.
-Center: Quantile-quantile plot of the Wald p-values applied to
-2,000 simulated datasets from \(\mathcal{MN}_{100\times 2}(\textbf{0}_{100\times
-2}, \textbf{I}_{100}, \sigma^2 \textbf{I}_{2})\). Right:
-Quantile-quantile plot of our proposed p-values applied to the same
-simulated datasets as in center.
+
+Figure 1: We simulated one dataset according to \(\mathcal{MN}_{100\times 10}(\textbf{\mu},
+\textbf{I}_{100}, \Sigma)\), where \(\mu_i = (1,0_9)^T\) for \(i=1,\ldots, 50\) and \(\mu_i = (0_9,1)^T\) for \(i=51,\ldots, 100\), and \(\Sigma_{ij} = 1\{i=j\}+0.4\cdot 1\{i\neq
+j\}\). (a): Empirical distribution of feature 2 based on
+the simulated data set. In this case, all observations have the same
+mean for feature 2. (b): We apply k-means clustering to obtain
+two clusters and plot the empirical distribution of feature 2 stratified
+by the clusters. (c): Quantile-quantile plot of naive z-test
+(black) our proposed p-values (orange) applied to the simulated data
+sets for testing the null hypotheses for a difference in means for
+features 2–8.
diff --git a/index.html b/index.html
index 1abde2b..786b748 100644
--- a/index.html
+++ b/index.html
@@ -66,7 +66,7 @@