Add paper and Poás field pictures

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     <title>Sarah Shi</title>
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@@ -176,7 +173,9 @@ <h2>Publications</h2>
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                 <h6> 
-                    [1, in review] 2023 <u><b>Shi, S.C.</b></u>, Towbin, W.H., Plank, T.A., Barth, A.C., Rasmussen, D., Moussallam, Y., Lee, H., Menke, W., <a class="custom-links" href="https://github.com/sarahshi/PyIRoGlass" target="_blank">PyIRoGlass</a>: An Open-Source, Bayesian MCMC Algorithm for Fitting Baselines to FTIR Spectra of Basaltic-Andesitic Glasses. <i><a class="custom-links" href="https://eartharxiv.org/repository/view/6193/" target="_blank">Volcanica</a></i>. 
+                    [2, submitted] 2024 Moussallam, Y., Towbin, W.H., Plank, T.A., Bureau, H., Khodja, H., Guan, Y., Ma, C., Baker, M.B., Stolper, E.M., Naab, F.U., Monteleone, B.D., Gaetani, G.G., Lee, H., Ding, S., <u><b>Shi, S.C.</b></u>, Rose-Koga, E.F., ND70 series basaltic glass reference materials for volatile elements (H<sub>2</sub>O, CO<sub>2</sub>, S, Cl, F) analysis and the C ionisation efficiency suppression effect of water in silicate glasses in SIMS analysis. <i><a class="custom-links" href="https://doi.org/10.31223/X5QQ4P" target="_blank">Geostandards and Geoanalytical Research</a></i>. <br>
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+                    [1, in review] 2023 <u><b>Shi, S.C.</b></u>, Towbin, W.H., Plank, T.A., Barth, A.C., Rasmussen, D., Moussallam, Y., Lee, H., Menke, W., <a class="custom-links" href="https://github.com/sarahshi/PyIRoGlass" target="_blank">PyIRoGlass</a>: An Open-Source, Bayesian MCMC Algorithm for Fitting Baselines to FTIR Spectra of Basaltic-Andesitic Glasses. <i><a class="custom-links" href="https://doi.org/10.31223/X55H4N" target="_blank">Volcanica</a></i>. 
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                 <h6>
-                [13, forthcoming] Tweedy, R., <u><b>Shi, S.C.</b></u>, Uno, K.T., Machine Learning Analysis of <i>n</i>-Alkanes from Woody and Grassy African Plants, NE GSA 2024 (<i>Talk</i>). <br>
+                [13] Tweedy, R., <u><b>Shi, S.C.</b></u>, Uno, K.T., Machine Learning Analysis of <i>n</i>-Alkanes from Woody and Grassy African Plants, NE GSA 2024 (<i>Talk</i>). <br>
 
                 [12] <u><b>Shi, S.C.</b></u>, Wieser, P., Toth, N., Antoshechkina, P., Lehnert, K., MIN-ML: Leveraging Machine Learning for Probabilistic Mineral Classification in Geochemical Databases, AGU 2023 (<i>Talk</i>). <br>
 
@@ -236,6 +235,32 @@ <h2>Field</h2>
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+                            <img src="img/DSC08759.jpg" alt=""> 
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+                <h6 style="text-align: center">Poás Volcano, Costa Rica </h6>
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@@ -372,6 +397,8 @@ <h2>Teaching</h2>
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                     I develop Jupyter notebooks to teach computational basics, statistical thinking, machine learning, and petrology. This work supports the educational goals of the <a class="custom-links" href="https://www.iedadata.org/" targe="_blank">IEDA2</a> data infrastructure, funded by the United States' National Science Foundation through a cooperative agreement. Please find these materials on my <a class="custom-links" href="https://github.com/sarahshi/earthchem-teaching" target="_blank">earthchem-teaching GitHub repository</a>. 
                     <br> <br>
+                    The python_fundamentals notebook was developed as an introduction to Python. We explore some basics with Python, NumPy, pandas, and matplotlib. <a href="https://colab.research.google.com/github/sarahshi/earthchem-teaching/blob/main/python_fundamentals.ipynb" target="_parent"> <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/> </a>
+                    <br> <br>
                     The SERC_MORB_colab notebook was developed for and taught to the Earth's Environmental Systems: Solid Earth course at Columbia University. The notebook provides code for visualizing and understanding trends in petrologic melt data. We explore global chemical variability in mid-ocean ridge basalts (MORB), understand variations in mantle melting temperatures, and think about what this all means for crustal thicknesses and seismic velocities. <a href="https://colab.research.google.com/github/sarahshi/earthchem-teaching/blob/main/SERC_MORB_colab.ipynb" target="_parent"> <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/> </a>
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                     The MINML_colab notebook was taught during the Goldschmidt 2023 Conference Workshop - Open Data in Geochemistry: Navigating Present Data Infrastructure and during the NFDI4Earth Lecture Series. The notebook provides code for visualizing and understanding trends in petrologic mineral data, and for utilizing machine learning to perform mineral classification. We explore large mineral datasets from PetDB and GEOROC. <a href="https://colab.research.google.com/github/sarahshi/earthchem-teaching/blob/main/MINML_colab.ipynb" target="_parent"> <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/> </a>