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Quality control and analysis of an updated wind gust data set in the United States
No full textThis thesis presents the development of an updated 51-year peak wind gust data set for 679 Automated Surface Observing Systems (ASOS) stations across the Continental United States (CONUS) and explores limitations and implications for long return period wind speed estimation. In total, the data set contains more than 17.9 million peak wind gusts, including nearly double the station-years available compared to the data set used in the current ASCE/SEI 7-22 wind hazard maps. A rigorous quality control methodology was implemented using manual inspection of archived Meteorological Aerodrome Reports (METAR), 1-minute ASOS data, radar data, and surface analysis. In addition, 1-minute data is used to explore how the automated quality algorithm and power outages may impact long return period wind speed estimations. Peak wind speeds are classified into thunderstorm, non-thunderstorm, and tropical and standardized for instrumentation changes.
Spatial analysis of annual maximum wind gusts shows the highest thunderstorm and non-thunderstorm wind speeds in the central Great Plains. Trends in median annual maximum wind gusts show a slight increasing trend, however, changes in ASOS averaging time and instrumentation, such as sonic anemometer installation, introduces three distinct eras in the data set.
Overall, this work represents the most complete data set ever assembled for CONUS ASOS stations and demonstrates improvements over the previous data set, improving confidence in extreme wind speed estimation for future wind hazard maps.Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-12-01The student, Michael Pagnanelli, Jr., accepted the attached license on 2025-12-11 at 16:28.The student, Michael Pagnanelli, Jr., submitted this Thesis for approval on 2025-12-11 at 16:56.This Thesis was approved for publication on 2025-12-12 at 08:20.DSpace SAF Submission Ingestion Package generated from Vireo submission #23140 on 2026-02-19 at 18:46:5
Functional and ecological investigations in Cucurbita: factors mediating fruit infections and insect interactions
No full textBacterial spot disease of cucurbits, caused by Xanthomonas cucurbitae, poses a significant threat to pumpkin production. This study aimed to investigate the role of the exocellulase gene cbhA in disease development by comparing a wildtype IL 234 4R isolate to a ΔcbhA mutant in greenhouse fruit inoculation trials. Eight experiments were conducted, including four with the wildtype isolate alone, and four comparing wildtype and mutant strains. Regression analysis of wildtype-inoculated fruit revealed a significant age-related resistance trend, with disease severity peaking at 10–12 days post-pollination. A quadratic model showed fruit age and bacterial concentration were strong predictors of disease area. Mutant-inoculated fruit exhibited weak, non-significant associations with age. Analyses indicated no statistically significant difference in disease severity between wildtype and mutant strains across experiments. Our results suggest cbhA is not essential for fruit pericarp infections but may play a role in vascular pathogenesis or possibly be compensated for by alternative virulence factors.
Cucurbit‐feeding beetles such as western corn rootworm, Diabrotica virgifera virgifera LeConte (Coleoptera: Chrysomelidae), spotted cucumber beetle Diabrotica undecimpunctata howardi Barber (Coleoptera: Chrysomelidae), and the striped cucumber beetle, Acalymma vittatum Fabricius (Coleoptera: Chrysomelidae). are major pests of pumpkins and related Cucurbita crops. We evaluated how floral resource availability and cultivar identity influenced beetle abundance across two field seasons on 16–21 pumpkin cultivars. Each season, randomized blocks of pumpkin cultivars were planted and sampled weekly over six weeks. We used statistical models to assess the effects of weekly flower count and sampling week on beetle abundance. We also screened greenhouse‐grown flowers of cultivars by ultra-performance liquid chromatography to quantify cucurbitacin B levels. Both flower availability and cultivar identity strongly influence beetle abundance. Although flowers provide essential feeding sites, inherent cultivar traits significantly modify attraction. These findings demonstrate selecting cultivars with lower beetle‐attraction profiles or pairing high‐cucurbitacin lines as trap crops could reduce pesticide reliance.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2027-12-01The student, Iris Lee, accepted the attached license on 2025-07-22 at 23:58.The student, Iris Lee, submitted this Thesis for approval on 2025-07-23 at 00:06.This Thesis was approved for publication on 2025-07-28 at 09:31.DSpace SAF Submission Ingestion Package generated from Vireo submission #22702 on 2026-02-19 at 20:07:5
In-situ impedance characterization for assessing SiC MOSFETs reliability
No full textThis dissertation presents an in-situ and online impedance characterization circuit for condition monitoring (CM) of Silicon Carbide (SiC) MOSFETs. The core concept involves injecting a pre-adjusted high-frequency current (≥ 2 MHz) into the device and isolating the resulting voltage component induced by this injection. By applying algebraic operations, the drain-to-source impedance is characterized and separated into its sub-components: on-state resistance and package inductance. Accelerated aging experiments confirm that on-state resistance correlates with gate-oxide degradation, while bond-wire lift-off leads to a measurable increase in package inductance. The circuit is thus capable of simultaneously tracking both degradation modes. Its performance is validated through extensive experimental setups including impedance analyzers, network analysis, oscilloscope waveforms, and x-ray imaging. In addition, the thesis proposes a scalable and galvanically isolated solution for monitoring multiple SiC MOSFETs operating in complementary configurations, enabling integration into practical converter topologies.
Gate-oxide degradation is evaluated using time-dependent dielectric breakdown testing, where gate-leakage current and on-state resistance are monitored. Results indicate that gate-leakage current remains in the sub-microampere range until the device fails abruptly, whereas on-state resistance exhibits a gradual increase due to growing trap concentration in the oxide. This makes on-state resistance a more practical precursor for early detection of gate-oxide degradation and preemptive device replacement.
Bond-wires represent another critical point of failure in SiC MOSFETs, largely due to the mechanical mismatch between aluminum wires and the SiC substrate. Thermal cycling over a device’s lifetime can cause fatigue at the solder joint, eventually leading to bond-wire lift-off. Even with multiple parallel wires, failure of one increases stress on the remaining wires and accelerates degradation. Package inductance, primarily shaped by bond-wire layout, is a unique and temperature-independent indicator of bond-wire integrity. A lift-off changes the current distribution and results in a step increase in inductance. Although this principle was known, no in-situ method previously existed. This work introduces the first in-situ and online solution capable of measuring package inductance with high sensitivity—detecting changes as small as 10 pH with 99 % confidence—as well as milliohm-level changes in on-state resistance.
Finally, the thesis presents a scalable, galvanically isolated monitoring solution tailored for complementary switch configurations commonly found in half-bridge, T-type, and neutral-point-clamp topologies. Instead of duplicating CM circuitry for each device, a single CM unit connects to complementary switches through a custom multi-port transformer. The proposed AC current-injection technique leverages the transformer windings for both current injection and voltage sensing. Because the transformer coils can float at arbitrary voltage levels, this system can monitor devices referenced to non-zero potentials. Electromagnetic design of a three-port transformer and a novel clamp-bias circuit are discussed in detail. The complete solution is experimentally validated on a SiC half-bridge operating at 800 V with 16 APP ripple current, successfully detecting individual bond-wire lift-off events on both high- and low-side devices.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2027-12-01The student, Furkan Karakaya, accepted the attached license on 2025-09-28 at 20:16.The student, Furkan Karakaya, submitted this Dissertation for approval on 2025-09-28 at 21:00.This Dissertation was approved for publication on 2025-09-30 at 11:55.DSpace SAF Submission Ingestion Package generated from Vireo submission #22816 on 2026-02-19 at 20:08:1
Chemomechanical modeling of hydrogen-induced degradation at high temperatures
No full textDegradation of structural materials by hydrogen gas at high temperatures poses serious challenges to the safety of hydrogen technologies operating at elevated temperatures such as solid oxide fuel and electrolyser cells, hydrogen gas turbines, etc. The objective of this dissertation is to develop mechanism-based methodologies for design of structural components exposed to hydrogen gas at high temperatures. Steel components exposed to hydrogen gas at high temperatures and pressures are particularly susceptible to a mode of degradation called High Temperature Hydrogen Attack (HTHA). During HTHA internal hydrogen reacts with carbides in the steel to form methane gas bubbles which results in decarburization and a loss in strength. These bubbles pressurized by methane gas can nucleate at grain boundaries and at particle/matrix interfaces. Adjacent bubbles grow and link up to form microcracks which can ultimately grow and can lead to fracture. The design of steel equipment against HTHA is primarily based on the use of the Nelson curves published by the American Petroleum Institute (API) which are empirical and do not account for the underlying failure mechanisms, the material microstructure, and the operating conditions, e.g., applied stress level and time. The API publication presents a series of Nelson curves specific to various steel compositions that are used extensively in the refining and petrochemical industries. These curves establish the safe operation regimes in a temperature vs. hydrogen pressure diagram. Despite the long-standing use of Nelson curves, recurring failures—notably the 2010 Tesoro accident—underscore the need for a deeper understanding of HTHA. With this pressing need for reliable design guidelines, this dissertation proposes methodology for mechanism-based assessment of material degradation.
Recent experimental evidence suggests that the nucleation and growth of HTHA-induced methane bubbles near pre-existing cracks are the most detrimental to material integrity. To this end, a fracture mechanics based methodology is proposed for reliability assessment of steel components. Simulations are conducted to predict methane bubble growth and coalescence near crack tips in 2.25Cr–1Mo steel under specified crack sizes in the inner diameter surface of a vessel, hydrogen pressures up to 20 MPa, and operating temperatures in the range of 400 to 600 °C. The model accounts for the coupled effects of creep and grain boundary diffusion, incorporating the influence of stress triaxiality ahead of the crack tip on bubble evolution. By treating the time to microcrack formation as a conservative estimate of component failure, Nelson-type curves were generated, mapping time to failure on hydrogen pressure–temperature diagrams for various crack sizes. These flaw-sensitive design curves represent a promising advancement over the empirical API Nelson curves, offering improved predictive capability while preserving the diagram's simplicity.
While most HTHA studies have focused on temperatures around 400–600 °C, carbon steels can experience HTHA damage at much lower temperatures as well—around 250 °C, at which the Tesoro accident occurred. We extend the fracture mechanics approach of design against HTHA to lower temperatures ~250 °C. To enable this design approach, two key developments are pursued. 1.) Existing models for methane gas generation during HTHA are based on very high-temperature (600–800 °C) experiments, which exceed typical HTHA conditions for carbon steels. We revisit the mechanism of methane formation in carbon steels, and a coupled chemical kinetics and micromechanics model is proposed which addresses methane and hydrogen gas formation along with simultaneous decarburization and bubble growth over a wide temperature range. The energetics of the chemical reactions taking place at the ferrite-matrix/bubble interface are established through atomistic calculations. Model calculations unveil the relationship between the rates of hydrogen migration to the bubble interface, carbon and hydrogen atom reactions for methane formation, and attendant volumetric bubble growth. 2.) Currently, little is known about the effect of hydrogen on the deformation of carbon steels at temperatures relevant to HTHA. To this end, a physically based constitutive model is developed which is based on the thermally activated motion of dislocations in the presence of hydrogen solutes. Through a series of stress relaxation and differential temperature experiments, the key role of hydrogen in aiding the motion of dislocations is identified. The constitutive model is implemented in a finite element program and is used to calculate the effect of HTHA on reduction of fracture toughness. The onset of crack growth is determined by the coalescence of a pre-existing crack tip with a nearby methane-filled grain boundary bubble, identifying a critical stress intensity factor.
From an operational standpoint, shutdown and startup activities are known to elevate the risk of HTHA failure, yet their impact remains unaccounted for in previous studies. We investigate the impact of shutdown/startup cycles on HTHA progression, emphasizing the thermo-chemo-mechanical effects of operational temperature and pressure fluctuations. Notably, during shutdown, methane-filled bubbles experience a drop in internal pressure due to cooling, however upon restart, this pressure is rapidly restored, creating mechanical cycling that can drive fatigue-like damage. This mechanism—previously unaddressed in HTHA literature—is demonstrated in this dissertation through simulations showing plastic strain jumps near bubble surfaces under repeated thermal cycles.
In addition to HTHA, hydrogen accelerates creep rupture in structural materials by increasing vacancy concentrations and enhancing dislocation climb. The last contribution of this dissertation is a physically based creep constitutive model rooted in the thermodynamics of hydrogen trapping at vacancies, providing a predictive framework for hydrogen-enhanced creep behavior at elevated temperatures. Based on experimental evidence, we posit that hydrogen’s influence on creep can be described by its effect on creep activation energy, specifically through its role in reducing the vacancy formation energy. The predictive capability of the proposed model is evaluated by comparison with creep experiments conducted on pure iron, which assess the effects of hydrogen pressure and temperature. The comparisons demonstrate excellent agreement of model predictions with experimental measurements, validating its applicability to predicting hydrogen-accelerated creep.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2027-12-01The student, Kshitij Vijayvargia, accepted the attached license on 2025-10-30 at 13:45.The student, Kshitij Vijayvargia, submitted this Dissertation for approval on 2025-10-30 at 13:47.This Dissertation was approved for publication on 2025-11-10 at 09:36.DSpace SAF Submission Ingestion Package generated from Vireo submission #22841 on 2026-02-19 at 20:08:3
Developing electrochemical methodologies towards addressing challenges in flow energy conversion technologies
No full textElectrolyzer technologies for sustainable fuel production face critical catalyst optimization challenges, particularly in developing energy-efficient alternatives to the oxygen evolution reaction that dominates electrolyzer energy consumption. This dissertation presents electrochemical methodologies developed to systematically address catalyst discovery and optimization for glycerol electrooxidation as a promising anodic reaction that can significantly reduce electrolyzer energy requirements while producing valuable chemicals from biomass waste. Beginning with fundamental interfacial characterization, an SECM-based spot analysis methodology was established that quantifies heterogeneous electron transfer kinetics and identifies deviations from ideal electrochemical behavior at carbon electrode interfaces. Building on these diagnostic capabilities, a modified flooded microwell SECCM approach was developed that overcame meniscus instability issues in alkaline media to enable screening of bimetallic catalyst arrays, demonstrating superior performance of Au-Pd systems over other bimetallic combinations for glycerol electrooxidation. However, the inherent limitations of scanning probe techniques—particularly restricted scalability, limited automation potential, and low experimental throughput—necessitated the development of more versatile screening architectures. To address these fundamental bottlenecks, an individually addressable electrode array methodology was implemented, which integrated with semi–automated synthesis and characterization protocols, enabled the successful screening of unique Au electrodeposition conditions and the identification of optimal parameters that correlate specific surface facets with electrocatalytic performance. This automated platform was extended to systematically evaluate 77 Au-Pd bimetallic compositions, revealing that ~45% Pd loading represents the optimal catalyst formulation that combines high activity, favorable kinetics, and great stability across multiple performance metrics. Validation through scaled-up flow electrolyzer experiments confirmed enhanced C-C bond cleavage activity and stable long-term operation, demonstrating successful translation from microscale screening to practical electrochemical systems. By systematically addressing the methodological bottlenecks that have constrained electrocatalyst discovery, this work provides scalable approaches for rational catalyst design that enable efficient biomass valorization in electrolyzer systems, contributing essential capabilities for sustainable chemical production and industrial decarbonization.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2027-12-01The student, Raghuram Gaddam, accepted the attached license on 2025-11-03 at 23:01.The student, Raghuram Gaddam, submitted this Dissertation for approval on 2025-11-03 at 23:09.This Dissertation was approved for publication on 2025-11-06 at 09:00.DSpace SAF Submission Ingestion Package generated from Vireo submission #22845 on 2026-02-19 at 20:08:3
Passivity, no-regret, and performance in online learning and games
No full textAs autonomous AI agents become more widely deployed across dynamic, multi-agent environments, they will continuously learn and interact in real time to achieve complex goals. This thesis develops a control- and game-theoretic foundation to analyze and ultimately synthesize such systems in which adaptive agents evolve in the presence of other adaptive agents. Building on this motivation, the thesis investigates the interplay between passivity, no-regret and performance of continuous-time learning dynamics. The analysis is divided into two parts: (i) the interaction between a learning model and a dynamic, uncertain environment, and (ii) the interaction among multiple adaptive learners within a game.
In the first part, the learning dynamic model is viewed as an input–output operator that maps the payoffs to strategies. Building on prior work for replicator dynamics, we show that if the learning dynamic model satisfies a passivity condition between the payoff vector and the deviation of its evolving strategy from any fixed strategy, it achieves finite regret. We then prove that this passivity condition holds for strategic higher-order variants of learning dynamics that have finite regret. We further provide numerical examples to illustrate the lack of finite regret of different evolutionary dynamic models that violate the passivity property. We also examine the fragility of the finite regret property under payoff perturbations. This raises an important question: is finite regret, by itself, a sufficient metric to assess the quality of the learning dynamic models , or should additional performance measures be considered? Motivated by this consideration, the thesis addresses the ``free-lunch'' question in no-regret learning- whether one no-regret algorithm outperform another in asymptotic average reward- so that an agent incurs regret for not having chosen a particular no-regret algorithm. We develop a control-theoretic lens in which a learning dynamic model is modeled as a cascade interconnection between a diagonal LTI map and the softmax nonlinearity, linking the frequency response (gain and phase) directly to asymptotic performance. We introduce payoff-based higher-order variants of replicator dynamics, anticipatory/predictive replicator dynamics, and show that the anticipatory model is dynamically equivalent to predictive replicator dynamics with a first-order low-pass predictor. An oracle (perfect-prediction) variant is proved to uniformly dominate the standard replicator dynamics, i.e., it achieves higher cumulative reward at every time horizon, across all environments. Using passivity, we cast the performance comparison as a passivity question: passivity of an associated comparison system is equivalent to uniform dominance of one learning algorithm over another. This yields several free-lunch results: predictive exponential replicator dynamics with a low-pass predictor uniformly dominates the standard exponential replicator dynamics for any payoff trajectory; moreover, any predictive replicator with a passive, asymptotically stable predictor, including anticipatory replicator dynamics, locally dominates the standard replicator. Framing the global comparison between anticipatory and standard replicator as an optimal-control problem, we show the minimal achievable performance gap is zero, implying uniform dominance of the anticipatory model across all environments. Lastly, we derive closed-form expressions for the long-run average reward and limiting strategy of replicator dynamics in arbitrary -periodic environments.
In the second part, the focus shifts from the interaction of a single learner with a dynamic environment to the interaction among multiple learners within a game. We establish a connection between finite regret and equilibrium-independent passivity (EI–passivity) through Best–Response Stationarity (BRS). Modeling the interaction between a learning dynamic (mapping payoffs to strategies) and a game (mapping strategies to payoffs) as a feedback interconnection, we exploit the fact that contractive games are anti–incrementally passive to show that incremental passivity is a stronger notion that implies both –passivity and EI–passivity. Based on this connection, we develop a passivity-based classification of learning dynamics according to the passivity notion they satisfy—namely, incremental passivity, –passivity, and EI–passivity—and use this classification as a framework for convergence analysis in contractive games. More generally, we develop an incremental-stability analysis for payoff-based higher-order variants of replicator dynamics in matrix contractive games.
Taken together, the results of this thesis provide a unified control-theoretic framework for analyzing and comparing the performance of online learning dynamics. Beyond the theoretical significance, these results bridge control theory, online learning, and game theory, offering concepts that can guide the design of stable, efficient, and robust autonomous learning systems operating in interactive, uncertain, and multi-agent environments.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2027-12-01The student, Hassan Abdelraouf, accepted the attached license on 2025-11-24 at 11:13.The student, Hassan Abdelraouf, submitted this Dissertation for approval on 2025-11-24 at 11:20.This Dissertation was approved for publication on 2025-11-26 at 11:21.DSpace SAF Submission Ingestion Package generated from Vireo submission #22881 on 2026-02-19 at 20:08:4
Multi-parametric photoacoustic/ultrasound localization (PAUL) imaging and its applications
No full textNoninvasive biomedical imaging technologies play a critical role in medical diagnostics, yet each modality has inherent limitations in spatial resolution, functional sensitivity, or molecular specificity. Hybrid imaging approaches have been developed to address these limitations, providing complementary structural and functional information for comprehensive tissue characterization.
This thesis introduces a dual-modal photoacoustic and ultrasound localization (PAUL) imaging platform that integrates super-resolution ultrasound localization (UL) with photoacoustic (PA) imaging to enable multiparametric sensing of anatomical, structural, functional, and molecular features. We developed multiple PAUL imaging strategies to enhance its capabilities, including fast imaging, 3D imaging with a large field of view, on-demand contrast generation, and fully label-free imaging without exogenous agents. The multiparametric sensing capability makes PAUL imaging well-suited to capture complex biological disease processes and guide therapeutic interventions. We further demonstrated this capability through several applications: noninvasive monitoring of focused ultrasound–induced blood–brain barrier disruption, longitudinal assessment of renal microvascular dysfunction in acute kidney injury, and image-guided mechanochemical cancer therapy.
Overall, this work establishes PAUL imaging as a high-resolution, versatile, and functional imaging platform for preclinical studies, offering new opportunities to probe vascular dynamics, tissue physiology, and therapeutic responses in vivo.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2027-12-01The student, Shensheng Zhao, accepted the attached license on 2025-11-20 at 00:08.The student, Shensheng Zhao, submitted this Dissertation for approval on 2025-11-20 at 00:21.This Dissertation was approved for publication on 2025-11-26 at 14:15.DSpace SAF Submission Ingestion Package generated from Vireo submission #22905 on 2026-02-19 at 20:08:5
Factors leading to employee engagement at work: insights from onsite study abroad staff members in Italy
No full textAccording to Gallup (2023c), 23% of the workforce from various not-mentioned industries in Europe, Africa, Asia, Australia, North America, and South America is unengaged at work, leading to quiet quitting and turnover and therefore costing the global economy about $8.8 trillion, which is 9% of global GDP. In addition, Gallup mentions Europe having the lowest percentage of engaged employees (at only 13%), with Italy ranked in 37th place (from 1-38) with only 5% of engaged employees. As a result, this study will explore the factors US-based study abroad institutions or organizations’ full-time on-site study abroad staff members in Italy, who provide students with services and support while abroad, perceive to lead them to be engaged at work.
Guided by Khan’s (1990) employee engagement theory, which draw directly from his conceptualization of employee engagement, this basic qualitative study used semi-structured interviews and thematic analysis, grounded in rich descriptions of 21 full-time on-site study abroad staff members in Italy collected in September to October 2024, to understand their personal experiences with engagement at work. The findings of the study indicated one overarching theme, which was positive workplace culture and seven subthemes, including purposeful variety; valued expertise; trust and support from supervisors and colleagues; job stability; schedule flexibility and work autonomy; physical, emotional, and mental well-being; and culturally competent staff.
The results of this study will help bridge the gap in research that focuses on sectors other than study abroad staff in Italy. Furthermore, the results will assist human resources (HR) and human resource development (HRD) at US universities with centers, offices, or teams in Italy,
US study abroad programs with centers or offices in Italy, and US study abroad providers with centers, offices, or teams in Italy recognize the importance of engagement of their on-site study abroad staff members to their organization or institution’s financial health. As a result, these HR and HRD professionals will take action and implement engagement strategies that will help decrease quiet quitting and turnover as well as ensure that their on-site staff members remain committed to their jobs, are productive while at work, and provide optimal customer service to maintain customer satisfaction and profitability. In turn, on-site study abroad staff members in Italy will feel at ease, enthusiastic to work, and satisfied with their jobs after the necessary strategies are implemented by HR and HRD.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2027-12-01The student, Aimee Devitto, accepted the attached license on 2025-11-20 at 12:04.The student, Aimee Devitto, submitted this Dissertation for approval on 2025-11-20 at 12:32.This Dissertation was approved for publication on 2025-12-02 at 09:13.DSpace SAF Submission Ingestion Package generated from Vireo submission #22912 on 2026-02-19 at 20:08:5
Скотский двор: Литературная генеалогия басни Дениса Фонвизина “Лисица-Казнодей”
Get PDFВ статье рассматриваются исторические и политические аллюзии в “поздней” политической басне Дениса Фонвизина (1745–1792), пережившего в период ее создания глубокий психологический и идеологический кризис, совпавший по времени с моральным кризисом триумфальной екатерининской империи. Автор показывает, что эта басня, вызванная к жизни актуальными современными событиями, является не столько свидетельством политической смелости писателя и его, по словам Г. А. Гуковского, “ненависти к деспотии” и “елейному” духовенству, сколько выражением презрительного примирения с действительностью, усталости и глубокого разочарования в возможности реализации политической программы, “завещанной” его патроном и вдохновителем Никитой Паниным. Вторая часть статьи рассматривает “посмертный” период существования этой басни, оставившей заметный след в русской политической истории
Tolerating monsters: Challenging extremism through animated storytelling
No full textThis paper discusses an anime course titled Tolerating Monsters: Challenging Extremism Through Animated Storytelling, which brings together monster theory, tolerance, critical media analysis, and cultural influence to explore anime’s pedagogical potential. The course examines how animated narratives, especially those featuring nonhuman and monstrous figures, can encourage students to think critically, challenge prejudice, and develop greater acceptance of difference. By highlighting anime as both a tool of critique and a reflection of ideologies, the course demonstrates how media can be used to foster understanding, reflection, and ethical awareness in the classroom