The Sensors, Energy, and Automation Lab (SEAL) aims to gamify undergraduate research by instituting a leaderboard, awarding points for tasks, assigning ranks for accomplishments and published papers, and framing research directions as Quests. Individuals receive a character sheet with a health bar, while groups compete against one another in Racetrack- a software for team challenges. Gamification in educational settings is well-studied: gamifying learning can boost students’ motivation, retention, and challenge appraisal. However, research indicates that the efficacy of gamification varies dramatically, particularly personality traits like extraversion, which correlate more positively with success in software with leaderboards. Significant gaps exist in gamification literature; existing research primarily studies gamification in classrooms, not workplaces or research environments. Further, the studies fail to incorporate modern approaches to psychology. The socio-psychological model suggests personalities and behaviors differ depending on the environment, meaning people may exhibit different personality traits in gamified environments. Moreover, gamer motivation, a personality test tailored to predicting player personality with strong correlations to the Big Five (psychological scale for key personality traits), has yet to be tested in gamification studies. By accounting for contemporary psychological theory, SEAL aims to rigorously test the hypothesis that gamification is an effective structure in lab organizations through multi-year longitudinal study on a scale never seen in gamification literature. SEAL’s large cohort and gamified structure offer a perfect platform to analyze the role of demographic and personality type in gamification outcomes. Our preliminary results explored collected qualitative and quantitative data on demographics, gamer motivation personality, and perceptions of the SEAL system by anonymously surveying 81 associates. Our longitudinal study contributes to the growing literature on gamification; a solution potentially improving productivity in research ecosystems.

The Pacific Northwest (PNW) saw an unprecedented heatwave between June 25 to July 3 of 2021, with temperatures reaching up to 15℃ above the climatological mean. Previous studies have focused on this event’s impacts on plants in Western Washington and Oregon through direct observations, or have focused on the economic implications from poor crop turnout. We used remote sensing data to take a holistic approach and examined how all plants throughout the PNW fared during and after this historical heatwave. We found that solar induced fluorescence (SIF) and near-Infrared reflectance of vegetation (NIRv), two remotely sensed vegetation health markers, had regionally dependent plant responses to the extreme heat. In particular, anomalously high SIF regions coincided with anomalously high photosynthetically active radiation (PAR) regions due to low cloud cover. As SIF has been used as a proxy for gross primary productivity (GPP), our findings begs the question: was the elevated SIF during the heatwave indicative of higher GPP, or was the SIF response an artifact of the higher radiation? Our study aims to further our understanding of how extreme events impact plant health, which is increasingly important as heatwaves become more intense and frequent in the future.

Nitrous oxide (N₂O) is an important greenhouse gas that depletes stratospheric ozone and is 300 times more potent than carbon dioxide (CO₂) over 100 years. Emissions have increased by 40% since 1980, and N₂O has been accumulating in the atmosphere at an unprecedented rate due to its long lifetime. The rapid rise of N₂O emissions primarily come from soil microbes that respond to the increased usage of agricultural fertilizers which help supply global food demand. Other notable sources include combustion, wastewater treatment, and industrial processes such as nitric acid production. Despite the importance of N₂O, atmospheric observations have limited spatial coverage. Remote sensing presents an attractive solution to dramatically increase spatial sampling. Here we assess the feasibility of using remote sensing to measure N₂O concentrations from sub-orbital platforms. Sub-orbital remote sensing platforms provide a testbed to determine the future viability of space-borne measurements. Our work uses an airborne instrument: the Airborne Visible InfraRed Imaging Spectrometer (AVIRIS). AVIRIS is a full spectral range airborne imaging spectrometer that measures the radiance of the Earth’s atmosphere from 380 - 2510 nm wavelengths. We hypothesize that band ratios from AVIRIS can be used to detect N₂O plumes. We begin by selecting the highest emitting point-source facilities in cloud-free flight tracks. Preliminary plumes will be verified by shape and direction according to meteorological data and consistency with facility layouts. We first test this methodology on CO₂, as previous studies have demonstrated successful detections with AVIRIS. CO₂ will serve as a proof of concept before applying our method to N₂O, which is more challenging to detect due to its lower atmospheric abundance and weaker spectral signature. 

The project aims to design a multi-modal sensor network with VLF antennas will be implemented to model the ionospheric D-region in real-time. In consideration of not having ground truth data, such a network will address the ill-posed problem of inverting with robust regularization techniques. High-data-rate acquisition, high-data-rate processing, and dynamically adaptable auto-tuning will be included in our design. Drawing on experience with the NeSSI, modularity and a digital bus for centrally processed, real-time processing will be part of a standardized, modular sensor network that will be designed. The D-region, an upper atmospheric dusty plasma, controls radio wave propagation via fluctuations in charge. Numerical simulations in our work simulate such occurrences as HF to UHF range radar echoes, validated through experiments in radar labs. Ionospheric instabilities in occurrences such as SAPS events generated through space weather result in GPS and Starlink communications outages. 3D electrostatic fluid and gyrokinetic equations are included in our model, which is significant for describing such instabilities. Real-time observation, predictive maintenance, and reliability in communications networks are enhanced through such studies.

Kaposi’s sarcoma (KS) is a cancer caused by Kaposi’s sarcoma-associated herpesvirus (KSHV). While most KS tumor cells are latently infected, where KSHV is inactive, all current treatments for herpesviruses target lytic infection. The Lagunoff lab has shown that latent KSHV infection, similarly to cancer cells, induces the Warburg effect, in which glycolysis is used as an energy source rather than oxidative phosphorylation. Inhibition of lactate dehydrogenase (LDH), an enzyme that catalyzes the last step of glycolysis, increases cell death specifically in latently infected cells. This indicated that the KSHV-induced upregulation of glycolysis was necessary for the survival of these cells; however, it is unknown how KSHV induces this requirement. The goal of my proposal is to determine the viral mechanism for the induction of the Warburg effect in latently infected cells. During latent infection, only the KSHV-latency-associated-region (KLAR) of the viral genome is expressed. KLAR encodes 4 genes: vFLIP, vCyc, LANA, the kaposins, and a cluster of 12 microRNAs. I hypothesized that one of the genes or miRNAs is necessary and/or sufficient to induce the requirement for glycolysis in latently infected cells. To test for necessity, I am using KSHV recombinant viruses that have a deletion in vFLIP, vCyc, the kaposins, or the entire miRNA locus to infect endothelial cells. To test sufficiency, our lab has created lentiviral vectors that contain one of the KLAR genes or the miRNA locus to overexpress these genes in endothelial cells. I anticipate that vCyc and/or the miRNA locus might exhibit necessity/sufficiency, since prior studies have identified these as important for the regulation of other metabolic pathways. Understanding KSHV’s alteration of specific metabolic pathways in latently infected endothelial cells provides novel therapeutic targets for the inhibition of latent KSHV infection and ultimately KS tumors.

Elevated levels of metals such as copper (Cu) and manganese (Mn) are often observed in liver failure patients, individuals with Wilson’s Disease, and those with hypermanganesemia with dystonia or workplace exposure. The binding of Cu and Mn to proteins such as albumin and ceruloplasmin poses difficulties for their removal through dialysis. The primary objective of this research is to evaluate the effectiveness of adding albumin in dialysis in removing these toxic metals. We explored different blood and dialysis flow rates and dialysate albumin concentrations to find optimal conditions for Cu/Mn removal. We also explored cheaper Food and Drug Administration (FDA) approved alternatives to albumin that may be effective at removing Cu/Mn. Additionally, due to Human Serum Albumin’s (HSA) limited supply and blood bank pricing, albumin from other mammal species were used to make treatments feasible. In this study we used albumin from several species and three low-cost albumin alternatives to remove Cu/Mn in a closed-loop dialysis process. We digested the biological samples with Nitric Acid and Hydrogen Peroxide on a hotplate and analyzed the atomic compositions of the biological samples using Inductively Coupled Plasma Mass Spectrometry (ICP-MS). We measured the percent reduction of each toxic metal normalized by albumin concentration and found that 20 mL/min and 150 mL/min of Bovine Serum Albumin (BSA) dialysate resulted in a significant percent reduction compared to the negative control. For albumin alternatives, Dextran Sulphate showed promise by notably increasing Cu percent reduction compared to the negative control. Despite the encouraging data, a larger sample size is needed to make a conclusive statement. Although Mn had little variance with different dialysate flow rates or albumin, charcoal columns demonstrated an effective near 100% reduction at both 20 mL/min and 120 mL/min of dialysate flow rate. Further replication studies are needed.

Mutations in the RAS gene family are common in various cancers and are estimated to occur in approximately 19% of cancer patients. We utilize the model organism C. elegans to study RAS genes because it sends signals in the worms the same way it does in humans. C. elegans only have one RAS family gene, encoded by let-60, making it simpler to study than the three in humans. The let-60 G13E mutation is a gain of function (gf) mutation also found in cancer patients and is characterized by a glycine to glutamic acid amino acid mutation at residue 13. The mutation is phenotypically marked by neoplasias - pathologically abnormal growths of tissue, effectively constituting tumors. Despite genetic uniformity of C. elegans in the controlled laboratory environment, not all let-60 gf worms develop neoplasias. Preliminary findings show that the penetrance of neoplasias is approximately 81% in the MT2124 strain, which developed the let-60 gf mutation via mutagenesis, and 93% in the ARM219 strain, which developed the mutation via CRISPR technology. Previous reports have identified chaperones as affecting RAS activity, My study aims to identify the effects of heat shock proteins hsp-17/CRYAB  and hsp-70/HSPA5 in C. elegans on the penetrance of neoplasias driven by the let-60 gf worms. Neoplasias shorten lifespan, so I measured their effects on survival in worms with and without the let-60 gf mutation, sorting them by tumor count. I hypothesized that the genetic backgrounds with a lower penetrance and expressivity of let-60 gf will have fewer tumors on average and observe a longer lifespan compared to strains with a higher penetrance of the mutation. Understanding the role of heat shock proteins in neoplasia penetrance could provide insights into potential therapeutic targets for RAS-related cancers.

Carbon fiber reinforced polymer (CFRP) is a composite material consisting of carbon fiber and cured resin layers. Its usage is especially prominent in Washington state, whose aerospace sector generates over 70 billion dollars in revenue each year and supports more than 250,000 jobs. Despite its relatively high material value of more than $40 per pound, around two million pounds of CFRP waste are sent to landfills in Washington each year. Assessments show that the costs of this waste and its disposal are a significant financial expense for manufacturers, potentially exceeding hundreds of thousands of dollars. Additionally, the complex and high-temperature manufacturing process required to produce CFRP is extremely energy intensive and generates high levels of greenhouse gas emissions. My research seeks to identify the current state of CFRP recycling in the Washington aerospace sector and examine its potential to address these industry-wide economic and environmental concerns. Through conducting market analysis of aerospace manufacturers in Washington, I will collect data on current levels of CFRP recycling and understand to what extent these recycling processes are effective in reducing environmental impact and improving business profitability. I aim to identify the main barriers that manufacturers face when attempting to implement recycling processes, in order to establish what developments would be necessary to expand the adoption of CFRP recycling across the industry. I anticipate that by identifying these developments and the processes required to achieve them, there will be opportunities for increased collaboration between aerospace manufacturers and CFRP recyclers. With Earth’s resources rapidly depleting and demand for CFRP steadily rising, CFRP recycling is a critical solution that will ensure that aerospace manufacturing can be sustainable, circular and economically feasible.

Sulfate aerosols cause pollution and affect climate by influencing cloud properties and incoming solar radiation. Emissions and abundances of sulfur-containing aerosols are one of the largest sources of uncertainties in global climate modeling. The largest biogenic and most uncertain emission source of sulfur aerosols is from phytoplankton in the form of dimethyl sulfide (DMS). In the atmosphere, DMS is oxidized to methanesulfonic acid (MSA) and other compounds that can form sulfate. Historical emissions of DMS are studied by measuring MSA concentrations in ice cores as a proxy for DMS oxidation. Declining levels of MSA have been found in ice core records, implying that production of DMS has also been decreasing; however, anthropogenically driven changes in atmospheric chemistry have altered the ratio of MSA to sulfate produced from DMS over time. To better understand DMS oxidation mechanisms and its relationship to the production of MSA and sulfate aerosols, we need more recent ice core records of MSA and sulfur isotopes of sulfate (δ³⁴S(SO₄^2–)) at higher temporal resolution. To measure δ³⁴S(SO₄^2–) at seasonal resolution in an ice core, rather than an annual resolution, the measurement size is smaller than previously measured by an order of magnitude, at about 1 µg S per sample. We will develop a new method to isolate samples containing less than 1 µg of sulfur from an ice core sample by separating SO₄^2– from other major ions in the sample using an ion chromatograph. We will quantify the isotopic ratio of sulfur in our samples by using an Orbitrap mass spectrometer. Quantifying sulfur isotopes at this resolution will provide information about the seasonality and change in phytoplankton sulfate production.