docs: update README;

README.md

@@ -1,13 +1,13 @@
 <a href="https://github.com/WenjieDu/PyPOTS">
-    <img alt="BrewPOTS logo" src="https://pypots.com/figs/pypots_logos/BrewPOTS_logo_FFBG.svg" width="180" align="right">
+    <img alt="BrewPOTS logo" src="https://pypots.com/figs/pypots_logos/BrewPOTS/logo_FFBG.svg" width="180" align="right">
 </a>
 
-<h2 align="center">Welcome to BrewPOTS</h2>
+<h3 align="center">Welcome to BrewPOTS</h3>
 
 *<p align="center">The tutorials help you brew Partially-Observed Time Series</p>*
 
 <a href="https://github.com/WenjieDu/PyPOTS">
-    <img src="https://pypots.com/figs/pypots_logos/PyPOTS_logo_FFBG.svg" align="left" width="128" alt="PyPOTS logo"/>
+    <img src="https://pypots.com/figs/pypots_logos/PyPOTS/logo_FFBG.svg" align="left" width="128" alt="PyPOTS logo"/>
 </a>
 In this project, partially-observed time series datasets are taken as coffee beans.
 As you can see, there is a coffee pot in the PyPOTS logo on the left,
@@ -20,6 +20,39 @@ You can tune the hyper-parameters by yourself to get better performance on the t
 
 Enjoy it! ☕️ And have fun!
 
+
+## ❖ Citing BrewPOTS/PyPOTS
+The paper introducing PyPOTS project is available on arXiv at [this URL](https://arxiv.org/abs/2305.18811),
+and we are pursuing to publish it in prestigious academic venues, e.g. JMLR (track for
+[Machine Learning Open Source Software](https://www.jmlr.org/mloss/)). If the tutorials in BrewPOTS are helpful to your work,
+please cite PyPOTS project as below and 🌟star this repository to make others notice it. 🤗 Thank you!
+
+<p align="center">
+<a href="https://github.com/WenjieDu/PyPOTS">
+    <img src="https://pypots.com/figs/pypots_logos/Ecosystem/PyPOTS_Ecosystem_Pipeline.png" width="95%"/>
+</a>
+</p>
+
+``` bibtex
+@article{du2023PyPOTS,
+title={{PyPOTS: a Python toolbox for data mining on Partially-Observed Time Series}},
+author={Wenjie Du},
+year={2023},
+eprint={2305.18811},
+archivePrefix={arXiv},
+primaryClass={cs.LG},
+url={https://arxiv.org/abs/2305.18811},
+doi={10.48550/arXiv.2305.18811},
+}
+```
+
+or
+
+> Wenjie Du. (2023).
+> PyPOTS: a Python toolbox for data mining on Partially-Observed Time Series.
+> arXiv, abs/2305.18811.https://arxiv.org/abs/2305.18811
+
+
 <details>
 <summary>🏠 Visits</summary>
 <a href="https://github.com/WenjieDu/BrewPOTS">