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AGGREGATION OF POLYDISPERSE VOLCANIC ASH PARTICLES UNDER TURBULENT AND MOIST CONDITIONS
Get PDFVolcanic eruptions may result in ash fallout with severe negative impacts on health, infrastructure, environment, and aviation. Volcanic ash transport and deposition (VATD) poses the most significant hazard in the case of eruption events. To mitigate these hazards and model ash transport and fallout accurately, comprehensive understanding the physical aggregation process of ash particles within volcanic plumes is of paramount interest. Even though there is a wealth of evidence in field observations supporting the aggregation of fine ash particles in water-rich volcanic plumes, most commonly employed ash transport codes neglect this agglomeration process. Ash particles finer than 125 μm largely settle out of the atmosphere as aggregates. As these aggregates are larger than single particles, they fall out of the atmosphere faster. Overlooking this premature fallout lead to systematic error in the prediction of ash dispersal.This study experimentally investigates two crucial factors that affect ash particle aggregation: 1. Liquid film coating on the particles in moist environments, as is expected in volcanic plumes with high water content; 2. The presence of turbulence which is ubiquitous inside volcanic plumes. The foremost objective of the work is to analyze and characterize the roles of these conditions in particle aggregation. A novel turbulence tower is used to simulate environments found inside volcanic plumes. This octagonal chamber employs carefully arrayed synthetic jet actuators to produce a nearly isotropic, homogeneous column of turbulence along the central axis of the tower. Tests are conducted under maximum turbulence, which has a Reynolds number, Reλ ≈ 240, with a corresponding Taylor microscale of 4.9 mm, at peak jet power (29 W), and under no turbulence conditions. Pre-chilled particles are allowed to fall through the tower under both turbulence intensities for a range of relative humidity levels, directly related to the particle liquid film thickness. Monodisperse solid glass spheres of̴ 40 μm diameter are used as ash particle analogs. Highly polydisperse volcanic ash collected from the 1980 eruption of Mount St. Helens are also tested extensively. For solid glass particles, the RH levels tested are 55%, 63%, 68%, 78%, 85%, and 95%. Two sets of tests are done at 55% and 63% and the data extracted are averaged. Volcanic ash particles are tested at 58%, 60%, 67%, 70%, 75%, 78%, 82%, 87%, 90%, and 93% RH levels.Aggregate samples are collected from these different conditions and microscopically imaged. These images are analyzed with a MATLAB image processing pipeline to extract information about the aggregation response of particles as functions of RH and turbulence levels. The results obtained demonstrate that monodisperse particle aggregation behavior adhere somewhat strictly to an upward trend for rising turbulence and humidity conditions. With the exception of a few unexpected surges and drops, increasing moisture content and turbulence lead to increasingly larger aggregate areas and perimeters and decreasing circularities. The probability distribution of aggregate sizes is also plotted.In significant contrast, it is observed that the aggregation behavior of polydisperse volcanic ash particles is complex and erratic, exhibiting stochastic sticking response. Only but a very weak upward trend can be discerned as relative humidity levels rise. The effect of turbulence on aggregation is even less obvious and appears seemingly random. Some suggestions for physically explaining these extreme fluctuations are ventured.Some of the limitations of this work are addressed in the conclusion section. It provides a reasonable framework for further studies attempting to quantify the effects of moisture and turbulence on volcanic ash particle aggregation behavior. The data obtained from this investigation and from similar experiments in the future may be implemented to refine existing ash transport codes to account for particle aggregation as a function of particle liquid coating thickness and turbulence.
EXTRUSION PROCESSING OF UPCYCLED ALMOND INGREDIENTS UTILIZATION OF ALMOND PROTEIN CONCENTRATE AND SKINS IN DIRECT EXPANDED PRODUCTS
Get PDFDirect expanded products are considered a major segment of extruded products made and consist of a large portion of the snack food market, both in the U.S. and internationally. The utilization of starch-rich matrices remains a crucial factor in determining the expansion potential, pasting characteristics, and overall quality of direct expanded products. Yet, continual use of primarily starch-based products also overlooks key nutritional benefits from other biopolymers and macronutrients, such as fiber and protein. As a result, ongoing research in finding compatible alternative ingredients for substitution or fortification continues to persist for better value addition of expanded products. Many alternative ingredients have been utilized in literature with varying results, being primarily dependent on the nutritional and functional properties of the ingredients. Thus, this research explores the utilization of byproduct almond ingredients, rich in protein and fiber, in direct expanded extruded products.The first study focused on the extrusion of pearled, short-grain white rice, utilizing a defatted almond protein concentrate flour with ~60% protein content (w/w). This protein flour is the result of upcycled almond press-cakes that were dried and further defatted, forming a stable flour. A Box-Behnken design was used to model the extrusion factors likely to impact extrudate qualities: inclusion level of the protein flour (5, 15, and 25% w/w), moisture content of the flour blend (18, 20, and 22% w.b.), and the screw speed of the extruder (300, 400, and 500 rpm). Modeled responses, with high R2 values, showed strong correlations between extrudate qualities (expansion ratio, water absorption and solubility, and extrudate color) and extrusion factors of influence. Higher % of almond protein inclusions showed higher potential for radial expansions, however also forming large non-uniform, and irregular extrudates. Higher inclusions of protein content also lowered the water absorption capacity of extrudates, while showing no influence on extrudate water solubility. The color of extrudates was influenced by all factors, showing the potential for Maillard browning interactions, dependent heavily on higher protein contents, low moisture, and high screw speeds. Overall, several interactions were observed with the inclusion of almond protein, resulting in varying expanded products of different qualities. Moisture content and screw speed were shown to be significant influences on product quality and may be able to balance negative attributes associated with an increase in protein content.The second study utilized a high-fat (~20% w/w) almond skin flour within a cornstarch base. These almond skins were a result of blanched almond byproducts, further dried and milled to a small particle size (median particle size D(50) = 424.20 ± 24.20μm). Keeping moisture content at a constant 16% w.b., which was shown to be ideal in the almond protein study, almond skin inclusion (5, 10, 15, and 20% w/w) and screw speed (150, 250, 350, 450 rpm) were chosen as main factors of influence. Almond skins were shown to have a significant influence (p>0.05) on radial expansion, water interactions, extrudate color, pasting characteristics, and energy applied to the extrusion system (SME). Overall, almond skins were shown to behave similarly to other non-soluble fibers, leading to reduced expansion and darkening of the extrudates with the increase in the inclusion levels. A low inclusion (5 – 10% w/w) however may be advantageous in expanding cornstarch extrudates, and at low screw speeds were shown to have larger radial expansions than the control (100% cornstarch). The use of these almond ingredients in extrusion may have similar characteristics in their disruption of the starch matrices, but present two different products. Depending on the final product vision, it is possible to at least utilize lower percentages of both ingredients (5-10%) for value addition without compromising overall extrudate quality
THE EFFECT OF STOKES NUMBER AND POLYDISPERSITY ON PREFERENTIAL CONCENTRATION AND AGGREGATION IN A PARTICLE-LADEN JET FLOW
Get PDFAsh transport and deposition from volcanic eruptions pose significant hazards to human health, infrastructure, and aircraft. Volcanic ash transport and deposition (VATD) models are essential tools to predict volcanic ash transportation and deposition. Particle size distribution is an important factor in modeling ash fall. Small particles can travel far and remain in the air for weeks. Larger particles fall faster and closer to the vent. Ash aggregation plays an important role in the overall size distribution of the volcanic ash cloud. Small particles can aggregate into larger ones and significantly influence ash settling behavior. Many factors, such as liquid bonding, electrostatic attraction, and preferential concentration due to turbulence, can influence the ash aggregation process. Despite the importance of ash aggregation, many VATD models do not incorporate this process accurately. To better represent aggregation dynamics in VATD models, this study investigates particle preferential concentration and aggregation through controlled laboratory experiments in relevant conditions.We investigate particle aggregation in a particle laden jet flow, which is analogous to the near exit region of a volcanic eruption. We eject compressed air and feed particles in controlled mass loadings into the jet stream to create particle laden flow. The study tests three particle types: hollow glass spheres, solid nickel spheres, and volcanic ash from the May 18, 1980 Mount St. Helens eruption. These particles vary in size distribution, shape, density, and electrostatic properties. The difference in types of particles allow us to investigate into how particle properties and polydispersity influence aggregation dynamics. Key flow variables are the Reynolds number (Re ~ 5000 to 10000) and Stokes number (St ~ 0.6 to 9.4 based on convective scale).The particles in the flow are illuminated by a laser, and a series of images are captured using a high-speed camera. Velocity profiles, turbulence characteristics, and preferentialconcentration of the particles in the jet flow are measured using Particle Image Velocimetry (PIV) and MATLAB image processing analysis, while the particles aggregates are collected in microscope slides and visualized with 100x zoom using a microscope. Particle overlapping with one another in the microscope slides can be falsely taken as aggregation when analyzing the images. This study proposes a method to normalize the experimental images with randomly distributed particles images in MATLAB to address the particle overlapping. We observe that in dry conditions, test runs with single type of particles lead to minimal aggregation. However, even in dry conditions, the test runs yield enhanced aggregation when there are hollow glass and nickel particles together in the jet. The tests with volcanic ash also show minimal aggregation in dry conditions. However, the size distribution used in the tests have a wide range (1μm to 1000μm) that can only produce qualitative results.Preferential concentration, or “clustering”, refers to locally dense concentrated particles in the flow. Turbulence can lead to preferential concentration in a jet flow. This study utilizes legacy PIV data to analyze preferential concentration in different Stokes number, Reynolds number, mass loading and relative humidity. We observe much more particle clustering in the flow when the Stokes number is close to one. We also observe that the clustering pattern is very similar when analyzing with normalized. The study also suggests some future directions to investigate the mechanisms for enhanced aggregation with two particle types
ULTRASTRUCTURAL DYNAMICS OF PHOTOSYNTHETIC THYLAKOID MEMBRANES IN VASCULAR PLANTS
Get PDFSessile photoautotrophic organisms, such as vascular plants, developed multiple-level adaptations for natural light energy fluctuations to sustain optimal energy conversion. The adaptations begin in chloroplasts on the thylakoid membrane, where the photosynthetic electron transport chain occurs. Plant thylakoid is a three-dimensional continuous membrane network hosting all protein complexes involved in photosynthetic light reactions and forming stacked grana of multiple tightly appressed thylakoid membrane discs interconnected by unstacked stroma lamellae. The two thylakoid domains host different sets of protein complexes and thus are involved in different parts of electron transport. The thylakoid is a highly dynamic network and undergoes dramatic short- and long-term light-induced adaptations. Because of the resolution needed to measure the fine ultrastructural features of thylakoids, the traditional method of choice has been transmission electron microscopy (TEM). We optimized reproducible TEM fixation for quantitative image analysis for the model plant Arabidopsis thaliana. We developed an automated Python-based image analysis pipeline to extract detailed Grana stack parameters quantitatively. The ImageJ Fiji-based semi-automated pipeline was designed to quantitatively analyze the entire thylakoid membrane and whole chloroplast parameters. These approaches were used to get insight into light-dependent ultrastructural adaptations and underlying mechanisms. We complemented the structural TEM information with a thorough biochemical analysis of thylakoids and thylakoid fractions to better understand the light-dependent structure-function relationship. To determine stoichiometric details of the main thylakoid photosynthetic protein complexes, light-harvesting complex II (LHCII), photosystem II (PSII), photosystem I (PSI), cytochrome b6f complex (cyt b6f complex), and ATPase, different quantitative spectroscopic and biochemical methods were optimized. We found a light-induced change in the thylakoid ultrastructure that consisted of a dramatic increase of stacked thylakoid doublets, a recently discovered membrane region having characteristics of both stacked and unstacked thylakoid regions that were previously suggested to be formed by specific LHCII thylakoid phosphorylation. Our experiments under moderate highlight confirmed that this light adaptation is controlled by thylakoid phosphorylation. The particular control, however, seems to be more complex since our experimental conditions exclude significant involvement of LHCII phosphorylation as the sole mechanism. Instead, our data show that light-dependent phosphorylation of PSII by STN8 kinase is involved in the thylakoid ultrastructural response under high-energy quenching conditions
METABOLIC ENGINEERING OF YARROWIA LIPOLYTICA AS A MICROBIAL CELL FACTORY FOR GLYCYRRHETINIC ACID BIOSYNTHESIS
Get PDFThe rising demand for plant-derived bioactive compounds has prompted the exploration of sustainable production alternatives. Glycyrrhetinic acid (GA), a pharmacologically valuable triterpenoid derived from licorice roots, faces production challenges due to low natural yields and complex extraction processes. This study focuses on engineering Yarrowia lipolytica, an oleaginous yeast with high acetyl-CoA flux, as a microbial cell factory for GA biosynthesis. A heterologous pathway incorporating four key genes—GgbAS1, CYP88D6, GuCPR1, and CYP72A63—was designed, codon-optimized, and assembled under strong constitutive promoters for expression in Y. lipolytica. The final construct (pCV316) was successfully integrated into the yeast genome using auxotrophic selection and validated by PCR and sequencing. GC-MS analysis confirmed the production of glycyrrhetinic acid in engineered strains. This work demonstrates the feasibility of microbial GA production using Y. lipolytica and lays the groundwork for future pathway optimization and scale-up, providing a promising alternative to traditional plant extraction methods
THE GENETIC DETERMINANTS OF POPULATION-LEVEL RESPONSES TO ENVIRONMENTAL CHANGE TESTS IN THREE PLANT SPECIES
Get PDFA major goal of evolutionary biology is to predict how organisms will respond to future environments. Predicting these evolutionary trajectories is often accomplished by looking for patterns of genetic variation left by past evolutionary forces, revealing evolutionary histories (e.g., founder events, degrees of connectivity) illuminating how populations may respond to future environments. Above all, there must be sufficient standing genetic variation for a population to evolve and continuously form new combinations of alleles necessary to meet the demands of novel environments. Second, evolutionary histories shape current population structures and offer signposts for future evolutionary trajectories. Environments therefore not only shape extant patterns of genetic variability and structure — they also provide a means to justify important determinants of fitness. The aims of this dissertation are to (i) characterize the genetic diversity in plant species endemic to steep elevation gradients in relation to past environments and (ii) evaluate possible future evolutionary trajectories given potentially adaptive patterns of genetic diversity. These two broad aims are achieved, with varying degrees of integration, in three dissertation chapters.First, we show that, after six generations and despite severely reduced genetic variation, a highly-selfing population of Mimulus guttatus shows small but significant responses to strong selection imposed on stigma-anther distance, a morphological trait related to breeding strategy (i.e., selfing or outcrossing). Second, we assessed the influence of elevation on population structure and signatures of adaptation within six populations of Cardamine cordifolia. Here, we found that low genetic variation among all study populations likely stems from a history of panmixia; future responses among all populations are likely to be the same, though may ultimately result in opposing fitness outcomes. Third, we used gene expression differences among five populations of Boechera stricta to test the influence of stark climatic gradients that are strongly correlated with elevation on signatures of adaptation. In this study, we found that there were differentially expressed genes among the populations that coincided with elevation. Functional enrichment of differentially expressed genes revealed that these genes were related to important environmental variables that are correlated with elevation. Altogether, the results of this dissertation highlight the utility of investigating patterns of genetic variation to hone predictions of population response to future environments
LEVERAGING MACHINE LEARNING TO IMPROVE EVAPOTRANSPIRATION ESTIMATION AND IRRIGATION SCHEDULING IN GRAPEVINES
Get PDFEffective irrigation scheduling depends on accurately estimating reference evapotranspiration (ETr), which is influenced by weather conditions and crop coefficients. Traditional models, such as the standardized Penman–Monteith equation (ASCE-PM), often yield unreliable results in hot, highly advective environments due to the empirical and mechanistic terms in its formulation. Additionally, the daily variability of water stress coefficients in grapevines remains underexplored. This study evaluates the potential of machine learning (ML) models as alternatives to ASCE-PM for estimating ETr across different temporal and spatial scales, assessing their transferability between regions, and exploring their application in quantifying actual evapotranspiration (ETa) in grapevines with improved stress detection. Meteorological data and lysimeter-measured ETr from well-watered alfalfa in Bushland, Texas (1996–1998), were used to develop and validate several ML models. These included support vector regression (GA-SVR), random forest (GA-RF), artificial neural networks (GA-ANN), and extreme learning machines (GA-ELM), each optimized using genetic algorithms. The models were trained to predict ETr at multiple timescales (daily, hourly, and quarter-hourly), and their performance was evaluated using RMSE, MAE, MBE, and R² metrics. Among these, the GA-ELM model achieved the highest accuracy, significantly outperforming the ASCE-PM standard. To improve spatial ETr estimation, the GA-ELM model was integrated into the METRIC (Mapping Evapotranspiration at High Resolution with Internalized Calibration) framework. The GA-ELM-calibrated METRIC model achieved an R² of 0.84 against lysimeter ET, compared to 0.74 for ASCE-PM, reducing estimation errors by up to 20%. To test model transferability, data from Bushland and Prosser, Washington, were analyzed using kernel density estimation and covariance analysis to examine the influence of meteorological variables on ETr. A semi-supervised learning approach was used to retrain the model using data from both sites. Results showed that temperature, relative humidity, and wind speed were key drivers of ETr at both locations. When tested on Bushland lysimeter data, the model achieved an MAE of 1.42 mm/day and an RMSE of 2.02 mm/day, demonstrating strong cross-regional performance. To estimate daily water stress coefficients (Ks) and their relationship to vine water status indicators, field experiments were conducted in a Cabernet Sauvignon vineyard in Prosser over three growing seasons (2022–2024), under three irrigation regimes: Full Irrigation (FI), Regulated Deficit Irrigation (RDI), and Drought Irrigation (DI). Periodic measurements included predawn (ψpd) and midday (ψmd) leaf water potential and drone imagery, while high-resolution data included soil water content and potential, sap flow, stem water potential (ψstem), and maximum daily shrinkage (MDS). ETa was estimated using sap flow (SapT), soil water balance (SWB), drone-based METRIC, the FAO method, and Ks-derived estimates. Ks was computed from normalized ψstem values in relation to relative soil water content (RSWC). Results indicated that ψpd was a more reliable indicator of vine water status than ψmd, with RSWC thresholds of 31.9% and 52.4% corresponding to ψpd values of –0.24 MPa and –0.16 MPa, respectively. Ks ranged from 0.37 to 1 across the seasons and responded to irrigation events when it dropped below 0.8. A strong relationship was observed between Ks and MDS. Although ET estimates varied significantly across methods, ETa was not significantly different but lower than ET estimates based on the FAO method. In contrast, it was significantly different from all the other methods. These findings highlight the value of integrating Ks with other soil and vine water status metrics to enhance irrigation scheduling–– an approach that provides a robust framework for improving vineyard water management through more precise ETa estimation and stress detection
ADVANCEMENTS IN DUAL-BAND AND WIDEBAND RF CIRCUIT DESIGN APPLICATIONS IN 5G AND ELECTROCHEMICAL SENSING ENSURING FOOD SAFETY
Get PDFThe increasing demand for high-performance RF circuit components and advanced electrochemical sensors has driven significant innovations in wireless communication and food safety monitoring technologies. As food safety concerns grow globally due to contamination risks from pesticides, antibiotics, heavy metals, and pathogens, there is an urgent need for real-time, accurate, and scalable monitoring solutions.RF circuit components—including power dividers, branch-line couplers, and RF energy harvesting systems—play a pivotal role in enabling wirelessly monitored sensors for food safety. Traditional electrochemical sensors, while highly sensitive, are often limited by wired data transmission, power constraints, and real-time applicability. The integration of RF technology into these sensors allows for wireless, remote monitoring, and IoT-enabled data transmission, significantly enhancing the efficiency, scalability, and automation of food safety monitoring systems. This thesis systematically investigates dual-band RF branch-line couplers (BLCs), wideband RF power dividers, and electrochemical sensing technologies, following a structured approach that begins with fundamental theoretical modeling and progresses toward practical applications. This research critically examines the potential enhancements RF techniques could offer to electrochemical sensing applications.The thesis begins by deriving a generalized equation for the Diagonal Crossed Dual-Band Branch-Line Coupler (DBBLC) to establish a fundamental theoretical framework. The power division characteristics of DBBLC are formulated using a systematic approach that considers even-even, odd-odd, odd-even, and even-odd mode analysis. The generalized susceptance equations derived in this study help in accurately determining the admittance transformation necessary to achieve arbitrary power division and impedance matching. By setting S11 = 0 and S41 = 0, the study obtains relations for equivalent conductance and susceptance, denoted as Geq and Beq, and expresses the power division ratio k in terms of characteristic impedances of the BLC core transmission lines. The findings demonstrate that DBBLC designs can achieve high-frequency operation with an output phase imbalance of only 1.95°, making them highly suitable for 5G FR2 applications operating at 28 GHz and 40 GHz. .Following the derivation of the generalized equation, the thesis advances toward handling complex structures by incorporating perturbation techniques alongside the previously established framework. The perturbation methodology is employed to optimize the design of Mid-Section Crossed Dual-Band Branch-Line Couplers (MBLCs) by introducing impedance-matching networks that minimize reflection and maximize isolation across dual bands. The proposed MBLC is capable of supporting an exceptionally wide band ratio of up to 11 and is fabricated on Rogers RO4003C substrates, with measurement results showing a magnitude imbalance of less than 4.Extending the principles of power division, the thesis then explores the design and miniaturization of a three-way power divider (3PD) to increase the number of output terminals while maintaining high performance. The proposed 3PD employs an eight-transmission-line structure, achieving up to 69.75. The results validate the proposed methodology as an effective means of achieving high-isolation and low-loss signal distribution in RF communication networks.In the final stage, the research expands beyond RF circuit design to explore the applicability of these findings in electrochemical sensor systems. While a direct integration of RF and electrochemical sensing is not proposed, the study conducts a critical review of electrochemical sensors for food safety and traceability. Electrochemical sensors, leveraging nanomaterials and conductive polymers, provide portable, real-time detection of contaminants such as pesticides, antibiotics, and heavy metals. However, existing sensor technologies face challenges in power efficiency, wireless transmission, and scalability. By reviewing the existing literature, this research identifies areas where RF techniques could enhance electrochemical sensor performance, particularly through RF energy harvesting for power-efficient sensing, microwave-assisted detection to improve signal transduction, and wireless transmission for RF-based monitoring systems. The proposed RF DBBLC and three way power dividers can wirelessly excite multiple electrochemical sensors simultaneously through near field/far field loop antenna and are able to extract and monitor useful sensing information through a RF signal reader such as Vector Network Analyzer (VNA) connected with the DBBLC or Power dividers.By following a structured progression from generalized theoretical modeling to advanced circuit design, miniaturization, and practical applications, this thesis presents a comprehensive framework for the development of multi-functional RF circuits while also identifying potential optimization strategies for electrochemical sensors. The findings contribute to the advancement of RF circuit technologies and offer valuable insights into the future possibilities of RF-assisted sensing systems. Through a combination of theoretical derivation, analytical modeling, perturbation-based design methodologies, and experimental validation, this research lays the foundation for future innovations in wireless communication and food safety monitoring offering solutions that are real-time, scalable, and highly efficient. This progress is crucial for ensuring global food security, improving human health, and reducing the burden of foodborne diseases, ultimately leading to a safer and healthier future for all
Long-distance Friends and Collective Action in Fisheries Management
Get PDFMuch received wisdom in the conservation literature is that individual connections across community boundaries undercut natural resource management. However, when multiple communities access the same resource, these long-distance relationships could generate interdependence and trust to motivate engagement in collective action to manage the resource. To test this, we interviewed 1317 people in 28 fishing villages in Tanzania about their participation in managing open-access fisheries and their social relationships in each village accessing the fishery. People with more friends in other villages trusted more people in those villages and were more likely to participate in collective action to manage the shared fishery, such as reporting others for destructive fishing practices. These results show that long-distance relationships may be a useful foundation upon which to build conservation efforts that cross community boundaries and bolster sustainable resource use
Finding Your Voice
Get PDFThe process of developing a compositional voice is not a clearly defined sequence of events. It is an experiential process that occurs when a composer creates a unique synthesis of compositional techniques that expresses their creativity while engaging the listener with a story that is sometimes entirely musical. The ability to use music to convey complex emotions or abstract ideas is not new territory. How that goal is achieved is something that is unique to each composer. Discovering the methods and techniques that create a person’s unique sonic voice/identity is a crucial part of the creative journey composers undertake and is a process of research, listening, and creating. This project covers all these aspects of compositional development that result in a performable product that not only shows the development of a choral composer but also a storyteller.This project is a culmination of research, composing, and writing that will result in a song cycle for SATB choir. The song cycle will feature the poetry of Emily Dickinson and Sara Teasdale, chosen for their writing style, and accessibility in the public domain. The purpose of this project is to synthesize research and discuss the compositional choices made while composing a song cycle for choir. The process of selecting poetry that evoked a theme or concept I wanted was challenging due to the large bodies of work from each poet, and narrowing those catalogs down to two poems by each composer was a highly involved process