diff --git a/_pages/dropdown.md b/_pages/dropdown.md
index 755337a..0f1ac8c 100644
--- a/_pages/dropdown.md
+++ b/_pages/dropdown.md
@@ -1,16 +1,16 @@
 ---
 layout: page
-title: submenus
+title: Others
 nav: true
 nav_order: 8
 dropdown: true
 children:
-  - title: Publications
+  - title: Books
     permalink: /publications/
   - title: divider
-  - title: Projects
+  - title: Journalism
     permalink: /projects/
   - title: divider
-  - title: Blog
+  - title: YouTube
     permalink: /blog/
 ---
diff --git a/_projects/1_project.md b/_projects/1_project.md
index 2aa8c1e..130d7a9 100644
--- a/_projects/1_project.md
+++ b/_projects/1_project.md
@@ -9,7 +9,6 @@ category: image analysis
 
 I am exploring ways to incorporate Point patterns analysis (PPA) for the analysis of microscopy images in neuroscience. PPA allows the investigation of the spatial arrangement/distribution of cells, like neurons and neuroglia, in the healthy and disease central nervous system. Indeed, it has application in multiple biomedical fields. I perform point pattern analysis using the [spatstat](https://spatstat.org/download.html) package in R-programming language. 
 
-</div>
 <div class="row">
     <div class="col-sm mt-3 mt-md-0">
         {% include figure.liquid loading="eager" path="assets/img/Pointanalysis.png" title="PPA" class="img-fluid rounded z-depth-1" %}
diff --git a/_projects/2_project.md b/_projects/2_project.md
index ae2d936..c8eed2b 100644
--- a/_projects/2_project.md
+++ b/_projects/2_project.md
@@ -4,12 +4,11 @@ title: Topological data analysis for neuroscience
 description: Implementation of Topological Data Analysis (TDA) to examine the spatial arrangement/distribution of cells. 
 img: assets/img/TDAimg.jpg
 importance: 2
-category: category: image analysis
+category: image analysis
 ---
 
 Topological data analysis (TDA) is an approach that uses algebraic topology to analyze complex data sets, including point clouds. With TDA, the user can evaluate the degree of noise, variability, and complexity, as well as identifying topological features such as holes, loops, and voids in the point clouds at different scales. This approach is based on tools like vietoris-rips complexes and persistent homology that allow to visualize complex topological structures.
  
-</div>
 <div class="row">
     <div class="col-sm mt-3 mt-md-0">
         {% include figure.liquid loading="eager" path="assets/img/TDAimg.jpg" title="example image" class="img-fluid rounded z-depth-1" %}