18 results on '"McGeachy, Alicia"'
Search Results
2. Multiscale characterization of shellfish purple and other organic colorants in 20th-century traditional enredos from Oaxaca, Mexico
- Author
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Vermeulen, Marc, Tamburini, Diego, McGeachy, Alicia C., Meyers, Rebecca D., and Walton, Marc S.
- Published
- 2022
- Full Text
- View/download PDF
3. Seventeenth-Century Barniz de Pasto Objects from the Collection of the Hispanic Society Museum & Library: Materiality and Technology.
- Author
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Basso, Elena, McGeachy, Alicia, Mieites Alonso, Maria Goretti, Pozzi, Federica, Radpour, Roxanne, and Katz, Monica
- Subjects
- *
REFLECTANCE spectroscopy , *RAMAN spectroscopy , *X-ray spectroscopy , *MASS spectrometry , *MATERIALITY & art , *FOOD aroma , *SPECTRAL imaging - Abstract
The Hispanic Society Museum & Library (HSML) holds a collection of nine viceregal barniz de Pasto objects, made by Indigenous artisans in the 17th and 18th centuries. Designed to imitate Asian lacquers and intended for European aesthetic tastes, barniz de Pasto is an example of Indigenous technique and knowledge that has survived to the present day. An in-depth analysis of five of these barniz de Pasto objects, dated to the first half and last quarter of the 17th century based on their iconography, was carried out through a combination of non-invasive and micro-invasive techniques, including portable X-ray fluorescence (pXRF) spectroscopy to investigate the possible presence of inorganic pigments, and fiber-optics reflectance spectroscopy (FORS) and reflectance imaging spectroscopy (RIS) to provide molecular information on colorants and their distributions across the objects. Dyes and pigments were also identified using Raman spectroscopy, Fourier-transform infrared (FTIR) spectroscopy, and liquid chromatography/mass spectrometry (LC/MS). The nature of the resin was determined by FTIR and pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS), while the decoration stratigraphy and composition were analyzed by scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDS). This paper confirms the use of mopa mopa, the resin used in the barniz de Pasto technique, in two objects not previously analyzed, and identifies indigo, insect-based red, calomel, lead white, and an unknown flavonol-based yellow dye, and challenges the use of calomel as a temporal marker for these works. Taken together, these results expand our understanding of the material use and explorations undertaken by artists during this time period to create such elaborate and enduring objects. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
4. Lipid Corona Formation from Nanoparticle Interactions with Bilayers
- Author
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Olenick, Laura L., Troiano, Julianne M., Vartanian, Ariane, Melby, Eric S., Mensch, Arielle C., Zhang, Leili, Hong, Jiewei, Mesele, Oluwaseun, Qiu, Tian, Bozich, Jared, Lohse, Samuel, Zhang, Xi, Kuech, Thomas R., Millevolte, Augusto, Gunsolus, Ian, McGeachy, Alicia C., Doğangün, Merve, Li, Tianzhe, Hu, Dehong, Walter, Stephanie R., Mohaimani, Aurash, Schmoldt, Angela, Torelli, Marco D., Hurley, Katherine R., Dalluge, Joe, Chong, Gene, Feng, Z. Vivian, Haynes, Christy L., Hamers, Robert J., Pedersen, Joel A., Cui, Qiang, Hernandez, Rigoberto, Klaper, Rebecca, Orr, Galya, Murphy, Catherine J., and Geiger, Franz M.
- Published
- 2018
- Full Text
- View/download PDF
5. Recent and Holocene climate change controls on vegetation and carbon accumulation in Alaskan coastal muskegs
- Author
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Peteet, Dorothy M., Nichols, Jonathan E., Moy, Christopher M., McGeachy, Alicia, and Perez, Max
- Published
- 2016
- Full Text
- View/download PDF
6. Can Deep Learning Assist Automatic Identification of Layered Pigments From XRF Data?
- Author
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Bingjie, Wu, Yunan, Hao, Pengxiao, Vermeulen, Marc, McGeachy, Alicia, Smith, Kate, Eremin, Katherine, Rayner, Georgina, Verri, Giovanni, Willomitzer, Florian, Alfeld, Matthias, Tumblin, Jack, Katsaggelos, Aggelos, and Walton, Marc
- Subjects
FOS: Computer and information sciences ,Computer Science - Machine Learning ,Computer Vision and Pattern Recognition (cs.CV) ,Image and Video Processing (eess.IV) ,FOS: Electrical engineering, electronic engineering, information engineering ,Computer Science - Computer Vision and Pattern Recognition ,Electrical Engineering and Systems Science - Image and Video Processing ,Machine Learning (cs.LG) - Abstract
X-ray fluorescence spectroscopy (XRF) plays an important role for elemental analysis in a wide range of scientific fields, especially in cultural heritage. XRF imaging, which uses a raster scan to acquire spectra across artworks, provides the opportunity for spatial analysis of pigment distributions based on their elemental composition. However, conventional XRF-based pigment identification relies on time-consuming elemental mapping by expert interpretations of measured spectra. To reduce the reliance on manual work, recent studies have applied machine learning techniques to cluster similar XRF spectra in data analysis and to identify the most likely pigments. Nevertheless, it is still challenging for automatic pigment identification strategies to directly tackle the complex structure of real paintings, e.g. pigment mixtures and layered pigments. In addition, pixel-wise pigment identification based on XRF imaging remains an obstacle due to the high noise level compared with averaged spectra. Therefore, we developed a deep-learning-based end-to-end pigment identification framework to fully automate the pigment identification process. In particular, it offers high sensitivity to the underlying pigments and to the pigments with a low concentration, therefore enabling satisfying results in mapping the pigments based on single-pixel XRF spectrum. As case studies, we applied our framework to lab-prepared mock-up paintings and two 19th-century paintings: Paul Gauguin's Po\`emes Barbares (1896) that contains layered pigments with an underlying painting, and Paul Cezanne's The Bathers (1899-1904). The pigment identification results demonstrated that our model achieved comparable results to the analysis by elemental mapping, suggesting the generalizability and stability of our model., Comment: 11 pages, 10 figures
- Published
- 2022
7. Denoising Fast X-Ray Fluorescence Raster Scans of Paintings
- Author
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Chopp, Henry, McGeachy, Alicia, Alfeld, Matthias, Cossairt, Oliver, Walton, Marc, and Katsaggelos, Aggelos
- Subjects
FOS: Computer and information sciences ,Computer Vision and Pattern Recognition (cs.CV) ,Image and Video Processing (eess.IV) ,FOS: Electrical engineering, electronic engineering, information engineering ,Computer Science - Computer Vision and Pattern Recognition ,Electrical Engineering and Systems Science - Image and Video Processing - Abstract
Macro x-ray fluorescence (XRF) imaging of cultural heritage objects, while a popular non-invasive technique for providing elemental distribution maps, is a slow acquisition process in acquiring high signal-to-noise ratio XRF volumes. Typically on the order of tenths of a second per pixel, a raster scanning probe counts the number of photons at different energies emitted by the object under x-ray illumination. In an effort to reduce the scan times without sacrificing elemental map and XRF volume quality, we propose using dictionary learning with a Poisson noise model as well as a color image-based prior to restore noisy, rapidly acquired XRF data.
- Published
- 2022
8. Can deep learning assist automatic identification of layered pigments from XRF data?
- Author
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Xu, Bingjie Jenny, Wu, Yunan, Hao, Pengxiao, Vermeulen, Marc, McGeachy, Alicia, Smith, Kate, Eremin, Katherine, Rayner, Georgina, Verri, Giovanni, Willomitzer, Florian, Alfeld, Matthias, Tumblin, Jack, Katsaggelos, Aggelos, and Walton, Marc
- Subjects
DEEP learning ,AUTOMATIC identification ,X-ray fluorescence ,PIGMENT analysis ,FLUORESCENCE spectroscopy ,MANUAL labor - Abstract
X-ray fluorescence spectroscopy (XRF) plays an important role for elemental analysis in a wide range of scientific fields, especially in cultural heritage. XRF imaging, which uses a raster scan to acquire spectra pixel-wise across artworks, provides the opportunity for spatial analysis of pigment distributions based on their elemental composition. However, conventional XRF-based pigment identification relies on time-consuming elemental mapping facilitated by the interpretation of measured spectra by experts. To reduce the reliance on manual work, recent studies have applied machine learning techniques to cluster similar XRF spectra in data analysis and to identify the most likely pigments. Nevertheless, it is still challenging to implement automatic pigment identification strategies to directly tackle the complex structure of real paintings, e.g. pigment mixtures and layered pigments. In addition, pigment identification based on XRF on a pixel-by-pixel basis remains an obstacle due to the high noise level. Therefore, we developed a deep-learning based pigment identification framework to fully automate the process. In particular, this method offers high sensitivity to the underlying pigments and to the pigments present in low concentrations, therefore enabling robust mapping of pigments based on single-pixel XRF spectra. As case studies, we applied our framework to lab-prepared mock-up paintings and two 19th-century paintings: Paul Gauguin's Poεave;mes Barbares (1896) that contains layered pigments with an underlying painting, and Paul Cezanne's The Bathers (1899–1904). The pigment identification results demonstrated that our model achieved comparable results to the analysis by elemental mapping, suggesting the generalizability and stability of our model. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
9. XRFast a new software package for processing of MA-XRF datasets using machine learning.
- Author
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Vermeulen, Marc, McGeachy, Alicia, Xu, Bingjie, Chopp, Henry, Katsaggelos, Aggelos, Meyers, Rebecca, Alfeld, Matthias, and Walton, Marc
- Subjects
- *
PYTHON programming language , *MACHINE learning , *INTEGRATED software , *X-ray fluorescence , *ELECTRONIC data processing , *IMAGE processing - Abstract
X-ray fluorescence (XRF) spectroscopy is a common technique in the field of heritage science. However, data processing and data interpretation remain a challenge as they are time consuming and often require a priori knowledge of the composition of the materials present in the analyzed objects. For this reason, we developed an open-source, unsupervised dictionary learning algorithm reducing the complexity of large datasets containing 10s of thousands of spectra and identifying patterns. The algorithm runs in Julia, a programming language that allows for faster data processing compared to Python and R. This approach quickly reduces the number of variables and creates correlated elemental maps, characteristic for pigments containing various elements or for pigment mixtures. This alternative approach creates an overcomplete dictionary which is learned from the input data itself, therefore reducing the a priori user knowledge. The feasibility of this method was first confirmed by applying it to a mock-up board containing various known pigment mixtures. The algorithm was then applied to a macro XRF (MA-XRF) data set obtained on an 18th century Mexican painting, and positively identified smalt (pigment characterized by the co-occurrence of cobalt, arsenic, bismuth, nickel, and potassium), mixtures of vermilion and lead white, and two complex conservation materials/interventions. Moreover, the algorithm identified correlated elements that were not identified using the traditional elemental maps approach without image processing. This approach proved very useful as it yielded the same conclusions as the traditional elemental maps approach followed by elemental maps comparison but with a much faster data processing time. Furthermore, no image processing or user manipulation was required to understand elemental correlation. This open-source, open-access, and thus freely available code running in a platform allowing faster processing and larger data sets represents a useful resource to understand better the pigments and mixtures used in historical paintings and their possible various conservation campaigns. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
10. Multi-Modal, Non-Invasive Investigation of Modern Colorants on Three Early Modern Prints by Maria Sibylla Merian.
- Author
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Dill, Olivia, Vermeulen, Marc, McGeachy, Alicia, and Walton, Marc
- Subjects
HYPERSPECTRAL imaging systems ,X-ray fluorescence ,PHOTOMETRIC stereo ,PRUSSIAN blue ,PIGMENTS - Abstract
Northwestern University's Charles Deering McCormick Library of Special Collections owns three hand-colored copperplate engravings that once belonged to an edition of Matamorphosis Insectorum Surinamensium by artist-naturalist Maria Sibylla Merian (1647-1717). Because early modern prints are often colored by early modern readers, or modern collectors, it was initially unclear whether the coloring on these prints should be attributed to the print maker, to subsequent owners or collectors, or to an art dealer. Such ambiguities posed challenges for the interpretation of these prints by art historians. Therefore, the prints underwent multi-modal, non-invasive technical analysis to assess the date and material composition of the prints' coloring. The work combined several different non-invasive analytical techniques: hyperspectral imaging (HSI), macro X-ray fluorescence (MA-XRF) mapping, surface normal mapping with photometric stereo, visible light photography, and visual comparative art historical analysis. As a result, the prints and paper were attributed to a late eighteenth-century posthumous edition of Merian's work while the colorants were dated to the early twentieth century. This information enables more thorough contextualization of these prints in their use as teaching and research tools in the University collection. [ABSTRACT FROM AUTHOR]
- Published
- 2021
- Full Text
- View/download PDF
11. Counting charges on membrane-bound peptides.
- Author
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McGeachy, Alicia C., Caudill, Emily R., Liang, Dongyue, Cui, Qiang, Pedersen, Joel A., and Geiger, Franz M.
- Published
- 2018
- Full Text
- View/download PDF
12. Hydrogen-Bond Networks near Supported Lipid Bilayers from Vibrational Sum Frequency Generation Experiments and Atomistic Simulations.
- Author
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Doğangün, Merve, Ohno, Paul E., Liang, Dongyue, McGeachy, Alicia C., Bé, Ariana Gray, Dalchand, Naomi, Tianzhe Li, Qiang Cui, and Geiger, Franz M.
- Published
- 2018
- Full Text
- View/download PDF
13. Single-component supported lipid bilayers probed using broadband nonlinear optics.
- Author
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Olenick, Laura L., Chase, Hilary M., Fu, Li, Zhang, Yun, McGeachy, Alicia C., Dogangun, Merve, Walter, Stephanie R., Wang, Hong-fei, and Geiger, Franz M.
- Abstract
Broadband SFG spectroscopy is shown to offer considerable advantages over scanning systems in terms of signal-to-noise ratios when probing well-formed single-component supported lipid bilayers formed from zwitterionic lipids with PC headgroups. The SFG spectra obtained from bilayers formed from DOPC, POPC, DLPC, DMPC, DPPC and DSPC show a common peak at ∼2980 cm
−1 , which is subject to interference between the C–H and the O–H stretches from the aqueous phase, while membranes having transition temperatures above the laboratory temperature produce SFG spectra with at least two additional peaks, one at ∼2920 cm−1 and another at ∼2880 cm−1 . The results validate spectroscopic and structural data from SFG experiments utilizing asymmetric bilayers in which one leaflet differs from the other in the extent of deuteration. Differences in H2 O–D2 O exchange experiments reveal that the lineshapes of the broadband SFG spectra are significantly influenced by interference from OH oscillators in the aqueous phase, even when those oscillators are not probed by the incident infrared light in our broadband setup. In the absence of spectral interference from the OH stretches of the solvent, the alkyl chain terminal methyl group of the bilayer is found to be tilted at an angle of 15° to 35° from the surface normal. [ABSTRACT FROM AUTHOR]- Published
- 2018
- Full Text
- View/download PDF
14. Quantifying the Electrostatics of Polycation-Lipid Bilayer Interactions.
- Author
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Troiano, Julianne M., McGeachy, Alicia C., Olenick, Laura L., Dong Fang, Dongyue Liang, Jiewei Hong, Kuech, Thomas R., Caudill, Emily R., Pedersen, Joel A., Qiang Cui, and Geiger, Franz M.
- Subjects
- *
CATIONS , *CELL membranes , *ELECTROMAGNETIC forces , *ELECTROSTATICS , *MOLECULAR interactions , *ALLYLAMINES - Abstract
Mechanistic insight into how polycations disrupt and cross cell membranes is needed for understanding and controlling polycation-membrane interactions, yet such information is surprisingly difficult to obtain at the molecular level. We use second harmonic and vibrational sum frequency generation spectroscopies along with quartz crystal microbalance with dissipation monitoring and computer simulations to quantify the interaction of poly(allylamine) hydrochloride (PAH) and its monomeric precursor allylamine hydrochloride (AH) with lipid bilayers. We find PAH adsorption to be reversible and nondisruptive to the bilayer under the conditions of our experiments. With an observed free adsorption energy of -52.7 ± 0.6 kJ/mol, PAH adsorption was found to be surprisingly less favorable relative to AH (-14.6 ± 0.4 kJ/mol) when considering a simple additive model. By experimentally quantifying the number of adsorbates and the average amount of charge carried by each adsorbate, we find that the PAH is associated with only 70% of the positive charges it could hold while the AH remains mostly charged while attached to the membrane. Simulations indicate that PAH pulls in condensed counterions from solution to avoid charge-repulsion along its backbone and with other PAH molecules to attach to, and completely cover, the bilayer surface. In addition, computations indicate that the amine groups shift their pK a values due to the confined environment upon adsorption to the surface. Our results provide experimental constraints for theoretical calculations, which yield atomistic views of the structures that are formed when polycations interact with lipid membranes that will be important for predicting polycation-membrane interactions. [ABSTRACT FROM AUTHOR]
- Published
- 2017
- Full Text
- View/download PDF
15. Resonantly Enhanced Nonlinear Optical Probes of Oxidized Multiwalled Carbon Nanotubes at Supported Lipid Bilayers.
- Author
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McGeachy, Alicia C., Olenick, Laura L., Troiano, Julianne M., Lankone, Ronald S., Melby, Eric S., Kuech, Thomas R., Ehimiaghe, Eseohi, Fairbrother, D. Howard, Pedersen, Joel A., and Geiger, Franz M.
- Subjects
- *
NONLINEAR optical techniques , *CARBON nanotubes , *BILAYER lipid membranes , *BIOLOGICAL systems , *HARMONIC generation - Abstract
With production of carbon nanotubes surpassing billions of tons per annum, concern about their potential interactions with biological systems is growing. Herein, we utilize second harmonic generation spectroscopy, sum frequency generation spectroscopy, and quartz crystal microbalance with dissipation monitoring to probe the interactions between oxidized multiwalled carbon nanotubes (O-MWCNTs) and supported lipid bilayers composed of phospholipids with phosphatidylcholine head groups as the dominant component. We quantify O-MWCNT attachment to supported lipid bilayers under biogeochemically relevant conditions and discern that the interactions occur without disrupting the structural integrity of the lipid bilayers for the systems probed. The extent of O-MWCNT sorption was far below a monolayer even at 100 mM NaCl and was independent of the chemical composition of the supported lipid bilayer. [ABSTRACT FROM AUTHOR]
- Published
- 2017
- Full Text
- View/download PDF
16. Impacts of climate and vegetation change on carbon accumulation in a south-central Alaskan peatland assessed with novel organic geochemical techniques.
- Author
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Nichols, Jonathan E, Peteet, Dorothy M, Moy, Christopher M, Castañeda, Isla S, McGeachy, Alicia, and Perez, Max
- Subjects
CARBON sequestration ,CLIMATE change ,PEATLANDS ,ORGANIC geochemistry ,HOLOCENE Epoch - Abstract
To constrain the effect of climate and peatland type on carbon accumulation, we reconstructed these parameters from a Holocene-length core of a Sphagnum-dominated peatland near Cordova, AK, USA. We determined peat type using a combination of peat texture and density, macrofossils, distributions of leaf-wax biomarkers, and soil pH reconstructions based on distributions of branched glycerol dialkyl glycerol tetraether lipids (brGDGTs). We produced an independent record of hydroclimate and temperature change using hydrogen isotope ratios of leaf-wax biomarkers and distributions of brGDGTs. Carbon accumulation rates were constrained with 14 AMS 14C dates from identified macrofossils and ash-free bulk density. In the early Holocene, the site was a shallow pond with evidence for emergent macrophytes, Sphagnum, and algae growing in a warm, moist climate. At 9.2 kyr (1 kyr = 1000 cal. yr BP), the site became a Sphagnum-dominated bog. Under mid-Holocene warm, evaporative climate conditions, the site became sedge-dominated. As climate cooled and effective precipitation increased, Sphagnum was able to gain dominance abruptly at ~3.5 kyr. Large changes in the vegetation assemblage and hydrology and climate are contemporaneous with significant changes in the rate of carbon accumulation. Carbon accumulated most rapidly when Sphagnum dominated and effective moisture was high and most slowly when sedges were dominant and conditions were warmer and drier. Estimates of future climate change indicate warmer, more evaporative conditions that, in the past, favored a sedge-dominated environment, suggesting that this peatland and those similar can contribute to a positive feedback to warming by transitioning to less efficient carbon sinks. [ABSTRACT FROM PUBLISHER]
- Published
- 2014
- Full Text
- View/download PDF
17. Shining Through: Multi-Analytical Studies of the Tiffany Hartwell Memorial Window.
- Author
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McGeachy, Alicia, Sabino, Rachel, McGoey, Elizabeth, and Walton, Marc
- Published
- 2021
- Full Text
- View/download PDF
18. Alteration of Membrane Compositional Asymmetry by LiCoO2 Nanosheets.
- Author
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Doğangün M, Hang MN, Troiano JM, McGeachy AC, Melby ES, Pedersen JA, Hamers RJ, and Geiger FM
- Subjects
- Cobalt chemistry, Lipid Bilayers chemistry, Membrane Potentials drug effects, Oxidation-Reduction drug effects, Oxides chemistry, Cell Membrane drug effects, Cobalt pharmacology, Nanostructures chemistry, Oxides pharmacology
- Abstract
Given the projected massive presence of redox-active nanomaterials in the next generation of consumer electronics and electric vehicle batteries, they are likely to eventually come in contact with cell membranes, with biological consequences that are currently not known. Here, we present nonlinear optical studies showing that lithium nickel manganese cobalt oxide nanosheets carrying a negative ζ-potential have no discernible consequences for lipid alignment and interleaflet composition in supported lipid bilayers formed from zwitterionic and negatively charged lipids. In contrast, lithiated and delithiated LiCoO2 nanosheets having positive and neutral ζ-potentials, respectively, alter the compositional asymmetry of the two membrane leaflets, and bilayer asymmetry remains disturbed even after rinsing. The insight that some cobalt oxide nanoformulations induce alterations to the compositional asymmetry in idealized model membranes may represent an important step toward assessing the biological consequences of their predicted widespread use.
- Published
- 2015
- Full Text
- View/download PDF
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