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TSSA: Two-Step Semi-Supervised Annotation for Radargrams on the Greenland Ice Sheet
(IEEE, 2023-07) Jebeli, Atefeh; Tama, Bayu Adhi; Janeja, Vandana; Holschuh, Nicholas; Jensen, Claire; Morlighem, Mathieu; MacGregor, Joseph A.; Fahnestock, Mark A.
Ice-penetrating radar surveys have been conducted across the Greenland Ice Sheet since the 1960s, producing radargrams that measure ice thickness and detect the ice sheet’s radiostratigraphy. However, these radargrams are relatively under-explored and not yet fully annotated, mapped, or interpreted glaciologically. We aim to move towards automatic radargram annotation using deep learning-based methods. To provide a training set for these methods, we develop a two-step semi-supervised annotation (TSSA) approach that uses an existing unsupervised layer annotation (ARESELP) method and a deep learning-based segmentation approach (U-Net) to detect surface, and bottom reflectors (representing the bedrock) layers in radargrams. Here we focus on two evaluations of our approach: 1. Surface and bottom annotations; and 2. Data augmentation and transfer learning techniques for improving the performance of deep learning methods. Our study is a foundation for improving the efficacy of AI-based methods for auto-annotation of radargrams, where the training set is generated seamlessly through unsupervised learning.
A Comprehensive View on TD Prevention Practices and Reasons for not Preventing It
(ACM, 2024-06-28) Freire, Sávio; Pacheco, Alexia; Rios, Nicolli; Pérez, Boris; Castellanos, Camilo; Correal, Darío; Rama?, Robert; Mandi?, Vladimir; Taušan, Nebojša; López, Gustavo; Mendonça, Manoel; Falessi, Davide; Izurieta, Clemente; Seaman, Carolyn; Spínola, Rodrigo
Context. Technical debt (TD) prevention allows software practitioners to apply practices to avoid potential TD items in their projects. Aims. To uncover and prioritize, from the point of view of software practitioners, the practices that could be used to avoid TD items, the relations between these practices and the causes of TD, and the practice avoidance reasons (PARs) that could explain the failure to prevent TD. Method. We analyze data collected from six replications of a global industrial family of surveys on TD, totaling 653 answers. We also conducted a follow up survey to understand the importance level of analyzed data. Results. Most practitioners indicated that TD could be prevented, revealing 89 prevention practices and 23 PARs for explaining the failure to prevent TD. The paper identifies statistically significant relationships between preventive practices and certain causes of TD. Further, it prioritizes the list of practices, PARs, and relationships regarding their level of importance for TD prevention based on the opinion of software practitioners. Conclusion. This work organizes TD prevention practices and PARs in a conceptual map and the relationships between practices and causes of TD in a Sankey diagram to help the visualization of the body of knowledge reported in this study.
Development of chemically crosslinked PEG-PAA hydrogels suitable for engineering of the vascularized outer retina
(ARVO, 2022-06-01) Pandala, Narendra; LaScola, Michael; Mulfaul, Kelly; Stone, Edwin M.; Mullins, Robert F.; Tucker, Budd A.; Lavik, Erin
To engineer a micorphysiologic system that more accurately recapitulates the vascularized outer retina suitable for evaluating AMD pathology and development of novel therapeutics. A hydrogel library based on poly (ethylene glycol) (PEG), poly-L-lysine (PLL) and poly(allylamine) (PAA) was generated using succinimide and free amine reaction chemistry. Cellular compatibility was evaluated using a rat endothelial cell line and human iPSC-derived choroidal endothelial cells generated via directed differentiation and CD31 magnetic bead immunopanning. Cell health and identity was evaluated using a series of live dead assays and immunofluorescence staining. A library of 12 synthetic, chemically crosslinked, hydrogels with tunable mechanical and degradation properties were developed. Hydrogels with a lower amine content were found to have superior endothelial cell compatibility. We hypothesize that this is due to the cell surface disrobing characteristics of the polycations presents in the gels. Hydrogels with a higher polycation concentration showed relatively poor endothelial cell compatibility. Gels with optimal compatibility were found to promote endothelial cell spreading, migration, and capillary network-like formation. In this study novel hydrogels with unique mechanical and degradation properties were generated via chemical crosslinking of PEG, PLL and PAA. Low amine hydrogels were found to be superior for promoting endothelial cell spreading, migration and vascular tube formation. To create in vitro models that more accurately recapitulate the choriocapillaris, optimized hydrogels will be used as a bioink for screen-based printing of rat and human vascular endothelial cells. This abstract was presented at the 2022 ARVO Annual Meeting, held in Denver, CO, May 1-4, 2022, and virtually.
Adopting Foundational Data Science Curriculum with Diverse Institutional Contexts
(ACM, 2024-03-07) Janeja, Vandana; Sanchez, Maria; Khoo, Yi Xuan; Von Vacano, Claudia; Chen, Lujie Karen
The prevalence of data across all disciplines and the large workforce demand from industry has led to the rise in interest of data science courses. Educators are increasingly recognizing the value of building communities of practice and adapting and translating courses and programs that have been shown to be successful and sharing lessons learned in increasing diversity in data science education. We describe and analyze our experiences translating a lower-division data science curriculum from one university, University of California, Berkeley, to another setting with very different student populations and institutional context, University of Maryland, Baltimore County (UMBC). We present our findings from student interviews across two semesters of the course offering at UMBC specifically focusing on the challenges and positive experiences that the students had in the UMBC course. We highlight lessons learned to reflect on the existing large scale program at UC Berkeley, its adaptation and opportunities for increasing diversity in new settings. Our findings emphasize the importance of adapting courses and programs to existing curricula, student populations, cyberinfrastructure, and faculty and staff resources. Smaller class sizes open up the possibility of more individualized assignments, tailored to the majors, career interests, and social change motivations of diverse students. While students across institutional contexts may need varying degrees of support, we found that often students from diverse backgrounds, if engaged deeply, show significant enthusiasm for data science and its applications.
Wearable sensors and infrared cameras: Introducing UMBC’s User Studies Lab
(UMBC News, 2020-02-05) Mastrola, Megan Hanks
Narrative to Trajectory (N2T+): Extracting Routes of Life or Death from Human Tra!icking Text Corpora
(2023-08-06) Karabatis, Saydeh N.; Janeja, Vandana
Climate change and political unrest in certain regions of the world are imposing extreme hardship on many communities and are forcing millions of vulnerable populations to abandon their homelands and seek refuge in safer lands. As international laws are not fully set to deal with the migration crisis, people are relying on networks of exploiting smugglers to escape the devastation in order to live in stability. During the smuggling journey, migrants can become victims of human trafficking if they fail to pay the smuggler and may be forced into coerced labor. Government agencies and anti- trafficking organizations try to identify the trafficking routes based on stories of survivors in order to gain knowledge and help prevent such crimes. In this paper, we propose a system called Narrative to Trajectory (N2T⁺), which extracts trajectories of trafficking routes. N2T⁺ uses Data Science and Natural Language Processing techniques to analyze trafficking narratives, automatically extract relevant location names, disambiguate possible name ambiguities, and plot the trafficking route on a map. In a comparative evaluation we show that the proposed multi-dimensional approach offers significantly higher geolocation detection than other state of the art techniques.
Audio deepfakes: A survey
(Frontiers, 2023-01-09) Khanjani, Zahra; Watson, Gabrielle; Janeja, Vandana
A deepfake is content or material that is synthetically generated or manipulated using artificial intelligence (AI) methods, to be passed off as real and can include audio, video, image, and text synthesis. The key difference between manual editing and deepfakes is that deepfakes are AI generated or AI manipulated and closely resemble authentic artifacts. In some cases, deepfakes can be fabricated using AI-generated content in its entirety. Deepfakes have started to have a major impact on society with more generation mechanisms emerging everyday. This article makes a contribution in understanding the landscape of deepfakes, and their detection and generation methods. We evaluate various categories of deepfakes especially in audio. The purpose of this survey is to provide readers with a deeper understanding of (1) different deepfake categories; (2) how they could be created and detected; (3) more specifically, how audio deepfakes are created and detected in more detail, which is the main focus of this paper. We found that generative adversarial networks (GANs), convolutional neural networks (CNNs), and deep neural networks (DNNs) are common ways of creating and detecting deepfakes. In our evaluation of over 150 methods, we found that the majority of the focus is on video deepfakes, and, in particular, the generation of video deepfakes. We found that for text deepfakes, there are more generation methods but very few robust methods for detection, including fake news detection, which has become a controversial area of research because of the potential heavy overlaps with human generation of fake content. Our study reveals a clear need to research audio deepfakes and particularly detection of audio deepfakes. This survey has been conducted with a different perspective, compared to existing survey papers that mostly focus on just video and image deepfakes. This survey mainly focuses on audio deepfakes that are overlooked in most of the existing surveys. This article's most important contribution is to critically analyze and provide a unique source of audio deepfake research, mostly ranging from 2016 to 2021. To the best of our knowledge, this is the first survey focusing on audio deepfakes generation and detection in English.
TSSA: Two-Step Semi-Supervised Annotation for Radargrams on the Greenland Ice Sheet
(IEEE, 2023-10-20) Jebeli, Atefeh; Tama, Bayu Adhi; Janeja, Vandana; Holschuh, Nicholas; Jensen, Claire; Morlighem, Mathieu; MacGregor, Joseph A.; Fahnestock, Mark A.
Ice-penetrating radar surveys have been conducted across the Greenland Ice Sheet since the 1960s, producing radargrams that measure ice thickness and detect the ice sheet’s radiostratigraphy. However, these radargrams are relatively under-explored and not yet fully annotated, mapped, or interpreted glaciologically. We aim to move towards automatic radargram annotation using deep learning-based methods. To provide a training set for these methods, we develop a two-step semi-supervised annotation (TSSA) approach that uses an existing unsupervised layer annotation (ARESELP) method and a deep learning-based segmentation approach (U-Net) to detect surface, and bottom reflectors (representing the bedrock) layers in radargrams. Here we focus on two evaluations of our approach: 1. Surface and bottom annotations; and 2. Data augmentation and transfer learning techniques for improving the performance of deep learning methods. Our study is a foundation for improving the efficacy of AI-based methods for auto-annotation of radargrams, where the training set is generated seamlessly through unsupervised learning.
Multi-domain Anomalous Relationships in Heterogeneous Temporal Data
(2023-12-06) Ale, Tolulope; Janeja, Vandana
The Arctic region is crucial to global climate stability. However, recent years have witnessed periods of extreme snow and ice melt, with rising temperatures that double the global average. These are not isolated events. They are the result of intricate interconnections across distinct domains. The challenge, therefore, lies not in understanding these individual domains, such as temperature, and radiation, but in decoding the inter-domain relationships inducing these polar anomalies. To address this, our study presents a novel framework aimed at mining these inter-domain relationships to explain such anomalies and the relationship across time series features comprehensively. These features may be selected from the same or different domains. Such anomalous relationships across features could help detect interesting phenomena such as extreme snow melt, and cloud cover and help identify time periods of interest when such relationships are more prevalent. We extracted the anomalous intervals in each domain using the Poisson Distribution model of rSatScan, then leveraged the concept of Direct Overlap and Proximity of anomalies to identify the direct and time-delayed temporal association (delayed correlation) between anomalies across features. The concept helps us understand how events in one domain may be associated with events in another domain during specific time periods using association rule mining. We evaluated our approach using ERA5 reanalysis data, and validated the identified anomalies against ground truth and evaluated the strength of the generated association rules using metrics like confidence and lift. Notably, several of our identified rules were consistent with findings confirmed by domain experts.
UMBC’s Vandana Janeja aims to boost high-performance computing know-how to tackle environmental science challenges with a $1 million NSF grant
(UMBC News, 2023-10-30) Meyers, Catherine
Discovering Portable Options through Automated Mapping
Topin, Nicholay; Haltmeyer, Nicholas; Squire, Shawn; Winder, John; MacGlashan, James; desJardins, Marie
Goal for artificial agents: Learn the most efficient process for completing a task in a given domain o Corollary: Reuse and transfer learned knowledge o Previous work assumed that a mapping was provided or that all domains were identical o Our contributions:  Automatically map across domains with different objects and attributes  Leverage prior knowledge by identifying commonalities between source and target domains  Provide novel techniques for scoring mappings and abstracting domains o Our method outperforms Pickett and Barto's PolicyBlocks (2002) and MacGlashan's Transfer Options (2013)
Game Changers
(UMBC Magazine, 2021-12-08) Lamb, Kennedy
Nanocapsules with HIF-1-alpha Inhibitor for Treatment of Choroidal Neovascularization in a Rat Model
(ARVO, 2023-06) Han, Ian; Pandala, Narendra; Maisha, Nuzhat; Ale, Tolulope; Mullins, Robert; Lavik, Erin; Tucker, Budd A.
Purpose : Choroidal neovascularization (CNV) is a vision-threatening complication of many retinal diseases, including age-related macular degeneration. Currently, the mainstay of CNV treatment is intravitreal delivery of antibodies that bind VEGF. However, there remains a great need for alternative therapies with longer duration and better treatment effect. This study describes the development of nanocapsule-based formulations toward sustained drug delivery of acriflavine (anti-angiogenic agent that inhibits hypoxia inducible factor [HIF]-1-alpha) and assesses its impact on CNV formation in a rat model. Methods : Polyurethane nanocapsules were synthesized by an interfacial condensation polymerization reaction in a nanoemulsion. Acriflavine was mixed with isophorone diisocyanate in water and then applied in drop-wise fashion to the solution before lyophilization to form drug capsules. Wild type Brown Norway rats were treated with laser photocoagulation to induce CNV. Eyes were injected intravitreally on the same day with 10 ul of either acriflavine nanocapsules (5 ug total dose of acriflavine) or blank nanocapsules as controls. Animals were assessed at 14-days post-injection with fundus photography, fluorescein angiography, and OCT (Figure). Eyes were enucleated for immunohistochemical analysis. CNV formation was compared between eyes treated with acriflavine versus blank nanocapsules. Results : Synthesis of acriflavine nanocapsules was reliable (Z-average diameter 197+/-39 nm) with a drug loading efficiency of 41 ug acriflavine/mg of nanocapsules. Following intravitreal injection, both nanocapsule formulations were well-tolerated, without signs of clinical inflammation or retinal toxicity. Visible intravitreal aggregates of nanocapsules were seen at 14-days post-injection. Preliminary qualitative analysis demonstrated markedly decreased sizes of CNV in acriflavine nanocapsules relative to fellow eye controls treated with blank nanocapsules (Figure). Conclusions : Nanocapsule formulations with acriflavine can be reliably manufactured with consistent drug dosing. Acriflavine nanocapsules are well-tolerated after intravitreal injection in an in vivo rat model and shows promise for inhibiting CNV formation. Studies are ongoing to quantify the effect of CNV inhibition at different dosages as well as various time points to evaluate drug duration.
Unaffected ex vivo clotting cascade by experimental hemostatic nanoparticles when introduced in the presence of recombinant tissue plasminogen activator
(Wolters Kluwer Health, 2022-12-06) Beyer, Margaret; France, John; Nagaraja, Tavarekere N; Lavik, Erin; Knight, Robert A; Lewandowski, Christopher A; Miller, Joseph B
CONTEXT: Hemostatic nanoparticles (hNPs) have shown efficacy in decreasing intracerebral hemorrhage (ICH) in animal models and are suggested to be of use to counter tissue plasminogen activator (tPA)-induced acute ICH. AIMS: The objective of this study was to test the ability of an hNP preparation to alter the clotting properties of blood exposed to tPA ex vivo. MATERIALS AND METHODS: Fresh blood samples were obtained from normal male Sprague-Dawley rats (~300 g; n = 6) and prepared for coagulation assays by thromboelastography (TEG) methods. Samples were untreated, exposed to tPA, or exposed to tPA and then to hNP. TEG parameters included reaction time (R, time in minutes elapsed from test initiation to initial fibrin formation), coagulation time (K, time in minutes from R until initial clot formation), angle (α, a measure in degrees of the rate of clot formation), maximum amplitude (MA, the point when the clot reaches its MA in mm), lysis at 30 min after MA (LY30, %), and clot strength (G, dynes/cm²), an index of clot strength. STATISTICAL ANALYSIS USED: Kruskal–Wallis test was employed to compare TEG parameters measured for untreated control samples versus those exposed to tPA and to compare tPA-exposed samples to samples treated with tPA + hNPs. Significances were inferred at P ≤ 0.05. RESULTS: Compared to untreated samples, tPA-treated samples showed a trend toward decreased angle and G suggesting potentially clot formation rate and clot strength. The addition of hNP did not affect any of these or other measured indices. CONCLUSIONS: The data demonstrated no hemostatic effects when the hNP was used in the presence of tPA. The lack of change in any of the TEG parameters measured in the present study may indicate limitations of the hNPs to reverse the thrombolytic cascade initiated by tPA.
Biocompatible Nanocapsules for Self-Healing Dental Resins and Bone Cements
(ACS, 2022-08-31) Menikheim, Sydney; Leckron, Joshua; Duffy, Michael; Zupan, Marc; Mallory, Amber; Lien, Wen; Lavik, Erin
Bone cements and dental resins are methacrylatebased materials that have been in use for many years, but their failure rates are quite high with essentially all dental resins failing within 10 years and 25% of all prosthetic implants will undergo aseptic loosening. There are significant healthcare costs and impacts on quality of life of patients. Self-healing bone cements and resins could improve the lifespan of these systems, reduce costs, and improve patient outcomes, but they have been limited by efficacy and toxicity of the components. To address these issues, we developed a self-healing system based on a dual nanocapsule system. Two nanocapsules were synthesized, one containing an initiator and one encapsulating a monomer, both in polyurethane shells. The monomer used was triethylene glycol dimethacrylate. The initiator capsules synthesized contained benzoyl peroxide and butylated hydroxytoluene. Resins containing the nanocapsules were tested in tension until failure, and the fractured surfaces were placed together. 33% of the samples showed self-healing behaviors to the point where they could be reloaded and tested in tension. Furthermore, the capsules and their components showed good biocompatibility with Caco-2 cells, a human epithelial cell line suggesting that they would be well tolerated in vivo.
PEGylated Polyester Nanoparticles Trigger Adverse Events in a Large Animal Model of Trauma and in Naıvë Animals: Understanding Cytokine and Cellular Correlations with These Events
(ACS, 2022-07-13) Maisha, Nuzhat; Kulkarni, Chhaya; Pandala, Narendra; Zilberberg, Rose; Schaub, Leasha; Neidert, Leslie; Glaser, Jacob; Cannon, Jeremy; Janeja, Vandana; Lavik, Erin
Intravenously infusible nanoparticles to control bleeding have shown promise in rodents, but translation into preclinical models has been challenging as many of these nanoparticle approaches have resulted in infusion responses and adverse outcomes in large animal trauma models. We developed a hemostatic nanoparticle technology that was screened to avoid one component of the infusion response: complement activation. We administered these hemostatic nanoparticles, control nanoparticles, or saline volume controls in a porcine polytrauma model. While the hemostatic nanoparticles promoted clotting as marked by a decrease in prothrombin time and both the hemostatic nanoparticles and controls did not active complement, in a subset of the animals, hard thrombi were found in uninjured tissues in both the hemostatic and control nanoparticle groups. Using data science methods that allow one to work across heterogeneous data sets, we found that the presence of these thrombi correlated with changes in IL-6, INF-alpha, lymphocytes, and neutrophils. While these findings might suggest that this formulation would not be a safe one for translation for trauma, they provide guidance for developing screening tools to make nanoparticle formulations in the complex milieux of trauma as well as for therapeutic interventions more broadly. This is important as we look to translate intravenously administered nanoparticle formulations for therapies, particularly considering the vascular changes seen in a subset of patients following COVID-19. We need to understand adverse events like thrombi more completely and screen for these events early to make nanomaterials as safe and effective as possible.
Azithromycin Protects Retinal Glia Against Oxidative Stress-Induced Morphological Changes, Inflammation, and Cell Death
(ACS, 2022-07-12) Mahaling, Binapani; Pandala, Narendra; Wang, Heuy-Ching; Lavik, Erin
The reactivity of retinal glia in response to oxidative stress has a significant effect on retinal pathobiology. The reactive glia change their morphology and secret cytokines and neurotoxic factors in response to oxidative stress associated with retinal neurovascular degeneration. Therefore, pharmacological intervention to protect glial health against oxidative stress is crucial for maintaining homeostasis and the normal function of the retina. In this study, we explored the effect of azithromycin, a macrolide antibiotic with antioxidant, immunomodulatory, anti-inflammatory, and neuroprotective properties against oxidative stress-induced morphological changes, inflammation, and cell death in retinal microglia and Müller glia. Oxidative stress was induced by H2O2, and the intracellular oxidative stress was measured by DCFDA and DHE staining. The change in morphological characteristics such as the surface area, perimeter, and circularity was calculated using ImageJ software. Inflammation was measured by enzyme-linked immunosorbent assays for TNF-α, IL-1β, and IL-6. Reactive gliosis was characterized by anti-GFAP immunostaining. Cell death was measured by MTT assay, acridine orange/propidium iodide, and trypan blue staining. Pretreatment of azithromycin inhibits H2O2-induced oxidative stress in microglial (BV-2) and Müller glial (MIO-M1) cells. We observed that azithromycin inhibits oxidative stress-induced morphological changes, including the cell surface area, circularity, and perimeter in BV-2 and MIO-M1 cells. It also inhibits inflammation and cell death in both the glial cells. Azithromycin could be used as a pharmacological intervention on maintaining retinal glial health during oxidative stress.
Hydroporphyrin-Doped Near-Infrared-Emitting Polymer Dots for Cellular Fluorescence Imaging
(ACS, 2022-04-22) Riahin, Connor; Meares, Adam; Esemoto, Nopondo Ndoh; Ptaszek, Marcin; LaScola, Michael; Pandala, Narendra; Lavik, Erin; Yang, Mengran; Stacey, Gary; Hu, Dehong; Traeger, Jeremiah C.; Orr, Galya; Rosenzweig, Zeev
Near-infrared (NIR) fluorescent semiconductor polymer dots (Pdots) have shown great potential for fluorescence imaging due to their exceptional chemical and photophysical properties. This paper describes the synthesis of NIR-emitting Pdots with great control and tunability of emission peak wavelength. The Pdots were prepared by doping poly[(9,9-dioctylfluorenyl-2,7-diyl)-alt-co-(1,4-benzo-(2,1′,3)-thiadiazole)] (PFBT), a semiconducting polymer commonly used as a host polymer in luminescent Pdots, with a series of chlorins and bacteriochlorins with varying functional groups. Chlorins and bacteriochlorins are ideal dopants due to their high hydrophobicity, which precludes their use as molecular probes in aqueous biological media but on the other hand prevents their leakage when doped into Pdots. Additionally, chlorins and bacteriochlorins have narrow deep red to NIR-emission bands and the wide array of synthetic modifications available for modifying their molecular structure enables tuning their emission predictably and systematically. Transmission electron microscopy (TEM) and dynamic light scattering (DLS) measurements show the chlorin- and bacteriochlorin-doped Pdots to be nearly spherical with an average diameter of 46 ± 12 nm. Efficient energy transfer between PFBT and the doped chlorins or bacteriochlorins decreases the PFBT donor emission to near baseline level and increases the emission of the doped dyes that serve as acceptors. The chlorin- and bacteriochlorin-doped Pdots show narrow emission bands ranging from 640 to 820 nm depending on the doped dye. The paper demonstrates the utility of the systematic chlorin and bacteriochlorin synthesis approach by preparing Pdots of varying emission peak wavelength, utilizing them to visualize multiple targets using wide-field fluorescence microscopy, binding them to secondary antibodies, and determining the binding of secondary antibody-conjugated Pdots to primary antibody-labeled receptors in plant cells. Additionally, the chlorin- and bacteriochlorin-doped Pdots show a blinking behavior that could enable their use in super-resolution imaging methods like STORM.
Highlighting the Usage of Polymeric Nanoparticles for the Treatment of Traumatic Brain Injury: A Review Study
(Elsevier, 2021-07) Onyeje, Chiad; Lavik, Erin
There are very limited options for treating traumatic brain injury (TBI). Nanoparticles offer the potential of targeting specific cell types, and, potentially, crossing the BBB under the right conditions making them an area of active research for treating TBI. This review focuses on polymeric nanoparticles and the impact of their chemistry, size, and surface groups on their interactions with the vasculature and cells of the brain following injury. The vast majority of the work in the field focuses on acute injury, and when the work is looked at closely, it suggests that nanoparticles rely on interactions with vascular and immune cells to alter the environment of the brain. Nonetheless, there are promising results from a number of approaches that lead to behavioral improvements coupled with neuroprotection that offer promise for therapeutic outcomes. The majority of approaches have been tested immediately following injury. It is not entirely clear what impact these approaches will have in chronic TBI, but being able to modulate inflammation specifically may have a role both during and after the acute phase of injury.
Storytelling for social justice and engagement: a materials science class
(ACS, 2021-09-08) Posey, Julianna; Lavik, Erin
The biographical stories of scientists and engineers, particularly those from historically excluded groups, have been integrated into the curriculum for a materials science course. The goal is to help students connect and relate to the scientific content, while opening the door to conversations about social justice in the virtual classroom. We have covered scientists including James Parsons, Hiroshi Amano, Evelyn Roberts, Wallace Carothers, Walter Hardenberg, and Max Liboiron. Furthermore, the technical information covered in the course has been contextualized by facilitating discussions on the history of certain raw material extraction and its ties to racism, colonialism, and the atrocities that result from these practices. This course was tailored to operate in an online setting by telling the stories of these scientists during lecture, and then asking students to express their learning through informal discussions and written reflections. This methodology encouraged conversations about inclusion and the role scientists must play as they consider both their work and the world around them, and students reported higher engagement and understanding between the technical science and the stories.

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