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Pretty and Problematic: The Use of Music in Guadagnino\u27s \u27Call Me by Your Name\u27
No full textTension in the reception of the American-Italian film Call Me by Your Name (dir. Guadagnino, 2017)—as a beautiful film that implicitly condones a problematic narrative—is shaped in part by its compilation soundtrack. Already lauded as a timeless masterpiece in cinematography, sensuality, and music, the film also receives steadfast criticism regarding its portrayal of homosexuality and alleged condoning of interage desire between Elio, a 17-year-old Italian-French boy, and Oliver, a 24-year-old American man. In this paper, I analyze five musical episodes from the film, including The Psychedelic Furs’ “Love My Way,” Ravel’s Une barque sur l’océan, and Sufjan Stevens’s “Mystery of Love” and “Visions of Gideon.” In each scene, I find that an aesthetic prioritization, an appeal to emotional universality, and/or a false portrayal of Elio as the primary initiator of intimacy all function to dismiss the problematic narrative and Oliver’s irresponsibility. In analyzing each work’s lyrics and/or narrative placement, I find that these instances enable for some viewers a harmful misunderstanding of modern queerness as pedophilic and indoctrinatory. Acknowledging recent homo/transphobic fearmongering in the guise of “child safety,” I remove the film’s rose-tinted glasses and reframe these scenes as tangible inspirations for real-life problems. Finally, I incite the reparative work of musicologist William Cheng to better interpret the film’s dilemma of the “pretty and problematic.” The film’s soundtrack simultaneously beautifies queerness and succumbs to weaponization against queerness; I argue that the film and soundtrack alike can be appreciated for their achievements and guide the work ahead of us
SMARCA1: A MASTER EPIGENETIC REGULATOR OF DIFFERENTIATION, EPITHELIAL-TO-MESENCHYMAL TRANSITION (EMT), AND THERAPEUTIC RESISTANCE IN RHABDOMYOSARCOMA
No full textThis dissertation characterized SMARCA1, an ISWI-family chromatin remodeler, as a multifunctional regulator in rhabdomyosarcoma (RMS), a pediatric cancer arising from the failure of muscle precursor cells to complete differentiation. Through comprehensive multi-omics approaches including CRISPR/Cas9 gene editing, RNA-seq, ATAC-seq, and CUT&RUN analyses, this work elucidates how SMARCA1 functions at the intersection of critical oncogenic pathways to influence differentiation, epithelial-to-mesenchymal transition (EMT), and therapeutic resistance. This research originated from a previous discovery of SMARCA1 as a binding partner of MyoG (unpublished data), which raised fundamental questions about its role in skeletal muscle and rhabdomyosarcoma. In this study, initial results revealed that SMARCA1 directly modulates chromatin accessibility and transcriptional activation of the tumor suppressor EGR1 and key Wnt signaling regulators, with a complex dose-dependent relationship between SMARCA1 levels and differentiation outcomes. Our work demonstrated that SMARCA5, another ISWI family member, primarily regulates cell proliferation and survival through the mTOR pathway. Initially guided by computational analyses of co-expression patterns, the role of SMARCA1 as a master regulator of EMT in fusion-positive RMS was confirmed in this study through next-generation sequencing approaches (RNA-seq, ATAC-seq, and CUT&RUN). These comprehensive genomic analyses revealed that SMARCA1 directly controls key EMT transcription factors (SNAI1, SNAI2, ZEB1, ZEB2, MYCN) and physically interacts with epigenetic modifiers like HDAC2 to coordinate TGF-β signaling through multiple pathways. Following SMARCA1 depletion, cell migration, invasion, and 3D spheroid formation were severely impaired, highlighting its essential role in maintaining the aggressive phenotype of RMS cells. This study further investigated therapeutic resistance mechanisms which revealed that SMARCA1 mediates resistance to MEK inhibitors in RMS subtypes. In fusion-positive RMS, SMARCA1 levels were observed to increase following trametinib treatment, and its knockout dramatically sensitized cells to MEK inhibition. The resistant cells showed extensive reprogramming, including global chromatin remodeling, enhanced expression of EMT factors, and activation of survival pathways including TGF-β and PI3K signaling. This work establishes SMARCA1 as a central epigenetic regulator in rhabdomyosarcoma with distinct yet interconnected functions contributing to pathogenesis and therapeutic resistance. The findings position SMARCA1 as a promising therapeutic target, particularly in combination approaches targeting the SMARCA1-TGFBR1 axis alongside MEK inhibitors to overcome the aggressive nature and treatment resistance of rhabdomyosarcoma
PREDICTION OF HORIZONTAL AND VERTICAL COMPONENTS OF EARTHQUAKE RESPONSE SPECTRUM USING SUPPORT VECTOR MACHINE
No full textSupport Vector Machine (SVM) is used to create ground motion models for the prediction of Horizontal component, vertical component and V/H ratio using 11,546 ground motion records obtained from the “Next Generation and the duration of Ground-Motion Attenuation Models” project. The predictor set considered in this research consists of the moment magnitude, dip angle, rake angle, depth to the top of fault rupture, Joyner Boore distance, closest distance to the ruptured fault area, and the shear wave velocity in the top 30 m of the site. SVM employs a kernel function to convert the data into a high-dimensional feature space, where linear modeling is carried out to address the difficulty associated with high nonlinear datasets. SVM was reasonably capable for prediction of both the horizontal and vertical component. However, prediction of V/H ratio was not accurate. The results illustrate SVM’s potential as a viable alternative to traditional ground motion prediction equations (GMPEs)
FROM PROPOSAL TO PRODUCTION: THE DEVELOPMENT PROCESS FOR THE PLAY, “THE MIND’S MIRAGE”
No full textToday is Penelope’s birthday and her friends, Tabitha and Addy, are hosting a party for her. An unwelcome guest upsets Penelope so much so, she does not want to attend. Her friends and her childhood doll, Ms Melanie-tonin, all confide her, trying to get her to join them, that is until, Tabitha provides a solution: a little candy, but not a sweet treat, but rather a substance to better relax Penelope. Through dream sequences, Penelope’s mind is revealed as she experiences her trip from bizarre nightmare encounters to a past spelling bee and even a breakup that continues to replay in her mind. The mirages of Penelope reality is portrayed all in her mind, but only in her mind. The questions of what is actually reality versus the her own perception as Penelope is schizophrenic
AI-ENHANCED DECENTRALIZED TASK ALLOCATION USING BLOCKCHAIN IN MULTI-ROBOT SYSTEMS
No full textJayaram Majeti, for the Master of Science degree in Computer Science, presented on March 31, 2025, at Southern Illinois University Carbondale.TITLE: AI-ENHANCED DECENTRALIZED TASK ALLOCATION USING BLOCKCHAIN IN MULTI-ROBOT SYSTEMS MAJOR PROFESSOR: Dr. Henry Hexmoor Multi-robot systems (MRS) are increasingly being deployed in dynamic environments such as disaster response, industrial automation, and autonomous transportation. Efficient task allocation is crucial for these systems to operate effectively. Traditional centralized task allocation methods suffer from single points of failure, limited scalability, and lack adaptability to changing environments. To address these limitations, this thesis proposes a decentralized AI-enhanced task allocation system using blockchain for secure coordination and reinforcement learning (RL) for adaptive bidding mechanisms. The proposed system leverages blockchain technology to ensure transparency, security, and decentralization, eliminating dependency on a single control entity. Simultaneously, reinforcement learning allows robots to learn from past allocations, improving task distribution efficiency over time. This hybrid approach enhances resilience, scalability, and adaptability in real-time applications. This thesis presents the system architecture, theoretical framework, and discusses future research directions in AI-driven decentralized task allocation
NATURAL LANGUAGE INTERFACE WITH MOBILE ROBOTS.
No full textMobile robots traditionally relied on programming languages for commands, which made them difficult to operate for non-experts. Without a Natural Language Interface (NLI), robots also struggled to perform tasks requiring multiple steps or understanding contextual nuances.This research aims to develop a Natural Language Interface (NLI) for mobile robots, eliminating the need for specialized programming knowledge and enabling intuitive human-robot interaction. The study compares a voice-controlled navigation system for two mobile robots, TurtleBot2i and ROSbot XL, by integrating Natural Language Processing (NLP) with the Robot Operating System (ROS).The system utilizes Large Language Models (LLMs) such as OpenAI’s Whisper and GPT-4o to convert speech into accurate robot commands, ensuring reliable execution even in noisy environments. Key innovations include real-time voice-to-command translation, the ability to handle informal commands, and dynamic audio feedback. This research presents a detailed analysis of the system\u27s architecture, the challenges faced, and the solutions implemented to create an efficient and user-friendly voice-controlled robotic interface
CRYSTALLIZATION OF PYRITE FROM ACIDIC HYDROTHERMAL SOLUTIONS
No full textThe crystallization of iron sulfides, such as pyrite and pyrrhotite, is of great significance due to their common association with most ore deposits around the world. Understanding the formation of these iron sulfides can give as insight into the genesis of the associated ore deposits. This study examines some of the factors influencing the crystallization of these iron sulfides from acidic hydrothermal solutions, with a focus on variations in solution composition and temperature. Under a well-controlled laboratory environment, the effect of variations in concentration and temperatures were studied. Analytical methods such as Scanning electron microscopy (SEM) and X-ray diffraction (XRD) were employed to measure crystal sizes and track morphological changes under various circumstances. The stability zones and crystal growth rates of pyrite and related minerals were determined through the application of the Scherrer equation. The results indicated that generally there was a strong correlation between the average pyrite crystal size and concentration of Fe in solution, but no strong correlation was observed in the average pyrrhotite crystal size and Fe concentration. It was observed that even for the pyrite, the correlation was strong in the lower temperatures (180⁰C and 200⁰C) for my studies but was moderate for the highest temperature(220⁰C). In contrast, the correlation between size and concentration for the pyrrhotite was very weak at the highest and lowest temperatures (180⁰C and 220⁰C) but was moderate at 200⁰C. This shows that concentration has an influence on the crystallization of the pyrite crystals but might not have a strong influence on the pyrrhotite. The findings in this work also suggested that, in general, lower concentration and higher temperature favored the formation of pyrite over pyrrhotite. These discoveries advance our knowledge of ore-forming settings and could be useful in mineral exploration, especially for deposits rich in iron sulfide. This research not only seeks to understand the influence of concentration and temperature on the crystallization of iron sulfides but also aims to serve as a launching pad to explore other parameters affecting their formation. Such insights could significantly benefit the geological and mining industries, as iron sulfides are commonly associated with ore deposits worldwide
When Spring Comes
No full textThis thesis is a finished draft of a fiction manuscript for a literary, historical novel with elements of a lesbian romance between Mai, a long-established errand girl and secret sex worker, and Xuân, a beautiful newcomer to the Inn, who has mysteriously waltzed through the Inn’s doors. This novel is set in a fictional village/mountain near Sapa, Vietnam, immediately after the French takeover of Vietnam as the country is split into Tonkin, Annam, and Cochinchina as a part of the French Indochinese Empire. This novel sets out to explore the themes of lesbianism in 20th century Vietnam, the disappearance of women in the merging of French colonialism and patriarchal centering of marriage in Vietnamese culture, and to explore what survival meant to queer, Vietnamese women in the early 20th century
IMPROVING DETECTION OF SOYBEAN SCN INFESTATION USING MULTI-SCALE REMOTE SENSING AND A NOVEL VEGETATION INDEX
No full textSoybean Cyst Nematode (SCN) is a pathogen with serious impacts on soybean yields. Traditional field-based assessment is labor-intensive and often ineffective for early interventions and the existing spectral vegetation indices (VIs) from remotely sensed data also lack the ability of accurately detect SCN infested plants. In this study, a greenhouse-based experiment was designed to collect a total of 100 hyperspectral data sets from 20 soybean plants from the 68th to 97th day after planting. Through statistical analysis, feature selection, and classification comparison of the hyperspectral data using seven classifiers, a new spectral VI, called SCNVI, was proposed based on the selected bands 338 nm and 665 nm. Three plant stress categories were defined based on initial egg inoculation levels: healthy (0 egg), moderate stress (1000 or 5000 eggs) and severe stress (10,000 eggs). The results showed that compared with the healthy plants, stressed plants significantly increased spectral reflectance in both UV and visible regions. ANOVA analysis indicated statistically significant differences in spectral reflectance among the three defined stress levels: healthy, moderate stress, and severe stress. Based on the significant bands identified through ANOVA (p \u3c 0.05), a Principal Component Analysis (PCA) was conducted, which showed that the first two components (PC1 and PC2) captured 97.18% of the total variance. Moreover, seven classifiers led to their top 10 bands selected with most of them falling in the region from 511 nm to 672 nm with several in the UV and red-edge region, such as 338 nm and 699 nm. Integrating each of the top 10 bands with seven classifiers resulted in an accuracy of 70% for distinguishing between healthy and stressed plants, but the accuracies of 40% to 60% for three-class classification. The SCNVI, coupled with eXtreme Gradient Boosting (XGBoost), achieved an accurate classification of 70% for three classes, and significantly outperformed the 13 traditional VIs by increasing the accuracy by more than 67%. Therefore, integrating the SCNVI and XGBoost algorithm provided great potential of improving detection of SCN infestation for soybean lands.To further evaluate the applicability of the proposed index in real-field conditions, a UAV-adapted version of the SCNVI (SCNVI_UAV) was developed for use with multispectral imagery, since typical UAV sensors do not capture the UV spectrum. In this adaptation, an alternative band 570 nm was used to approximate the sensitivity normally provided by the UV band. The UAV-derived SCNVI time series data were clustered into three groups representing healthy, moderate stress and severe stress levels. Statistical validation showed a strong correlation between the SCNVI_UAV-based clusters and field-observed SCN egg counts, with significant differences between clusters (p \u3c 0.05). Overall, integrating the hyperspectral-derived SCNVI with advanced machine learning techniques and adapting the index for UAV platforms provides a promising foundation for the early detection and management of SCN infestations, ultimately contributing to more sustainable soybean production