80264 research outputs found
Sort by
Machine Learning for XENONnT and Bayesian Inference in Astroparticle Physics
No full textThis thesis presents a series of studies conducted within the XENONnT experiment, a dark matter direct detection experiment using a dual-phase liquid xenon time projection chamber detector. The focus is on data processing, signal reconstruction, and the application of machine learning techniques to improve event localization and statistical inference.
A multilayer perceptron and a domain-informed neural network were developed and trained for S2 position reconstruction, significantly enhancing spatial resolution. These models were validated using experimental data, leading to the design of a new data selection cut to refine event reconstruction. Additionally, preliminary investigations into anode shadowing, light collection efficiency map modeling, and saturation effects provide insights for future research.
Beyond position reconstruction, this work explores the application of normalizing flows to accelerate statistical inference in neutrino non-standard interactions (NSI). The results demonstrate that reparameterization using normalizing flow can improve the efficiency of posterior sampling, offering a promising approach for future constraints on NSI parameters using XENONnT data
The Influence of Antidepressants on Emotional Memory and Medial Temporal Lobe Function
No full textDepression is a debilitating mood disorder, associated with impaired memory and a negativity bias, where negative events are better remembered than positive or neutral events. Impaired hippocampal pattern separation, a computation supporting memory for unique events, has been proposed as a mechanism underlying cognitive dysfunction in depression. Mnemonic discrimination tasks tax hippocampal pattern separation, offering insight into mechanisms underlying memory deficits in depression. Antidepressants are the first-line pharmacological treatment for depression and target specific neurotransmitters that can impact the hippocampus and surrounding medial temporal lobe regions. However, there is limited research examining the influence of antidepressants on memory and hippocampal function in humans. This study utilized high-resolution neuroimaging to examine hippocampal activity during emotional memory in individuals taking antidepressants. Results showed differing hippocampal activity based on antidepressant type and treatment response, suggesting that these factors can have unique impacts on emotional memory and the underlying neural mechanisms of depression
Olvidar
No full textMy dissertation is an orchestral work titled Olvidar (“to forget”) that explores the fluid and fragmented nature of memory, portraying its transformations through shifting textures, evolving harmonic fields, and timbral contrasts. The piece navigates the tension between recollection and erasure, employing recurring motifs that dissolve and re-emerge in altered forms to reflect the instability of remembered experiences. Through the weight of the full orchestra—pulsing like a heartbeat—and its eventual dissolution into lightness, Olvidar captures the contrast between the burden of memory and the release of forgetting, shaping how the past lingers within the present
What makes a good leader: Validation of a situational judgment test to assess leader behavioral knowledge
No full textLeadership behavior is a critical reflection of one’s leadership capability. Notably, having knowledge of leadership behaviors contributes to actually enacting these behaviors. Thus, the purpose of the current research is to validate a situational judgment test (SJT) measure to assess leadership behavioral knowledge. The first study aims to establish a multidimensional framework of leadership behaviors based on Campbell’s Model of Leader Performance (2012) and leadership inclusion behaviors toward diversity, equity, and inclusion (Shore et al., 2011; Silver et al., 2022). Using this framework, the second study proceeds to validate a SJT measure of leadership behavioral knowledge. Study findings suggest evidence supporting the multidimensional framework of leadership behaviors, in addition to the need for further refinement and validation of the SJT leadership measure. Altogether, the findings contribute to theoretically informing the construct space of effective leadership, in addition to providing practical guidance for developing a leadership assessment to be used for future leader selection, training, and development
Structure and Perception: The Rhythmic Canon in the Music of Olivier Messiaen
No full textIn the early to mid-twentieth century, an increased interest in complex rhythmic structures led to a resurgence of interest in the rhythmic canon. Olivier Messiaen was an influential innovator and practitioner of this technique, incorporating rhythmic canons in many of his works. Messiaen’s most important contribution was to treat rhythm as a parameter independent of pitch that could undergo complex development within a canonic structure on its own terms. In this document, I examine Messiaen’s rhythmic canons in the context of his broader compositional language, exploring their structure, formal function, and perceptual implications. First, I survey Messiaen’s compositional techniques most relevant for his canonic writing. Then, I propose a typology for analyzing Messiaen’s canons and discuss examples within each type: pitch canons, rhythmic canons by displacement, rhythmic canons by augmentation, and rhythmic canons by retrograde. Analysis of individual canons reveals how Messiaen’s compositional decisions respond to the compositional and perceptual tendencies inherent to each type of canon, and the proposed typological framework lays the groundwork for a better understanding of the general musical possibilities of the rhythmic canon
A Computational and Experimental Investigation of Guanine Functionalization of Single-Walled Carbon Nanotubes
No full textSingle-walled carbon nanotubes (SWCNTs) have garnered significant attention over the past two decades due to their exceptional physical properties and promising applications in biomedical theranostics and nanoelectronics. Recent findings have shown that the exciton band gap of semiconducting SWCNTs can be spatially modulated through a chemical process known as guanine functionalization. In this mechanism, guanine nucleotides from an ssDNA strand wrapped around the nanotube covalently bond to the sidewall carbon atoms when exposed to singlet oxygen.
This dissertation advances the understanding of guanine functionalization of SWCNTs by exploring physical properties, reaction kinetics, and mechanisms. We investigate kinetic and thermodynamic parameters like activation energy and well depth at functionalization sites. Temporal studies reveal a shift from sp³ to sp² hybridization at guanine-functionalized sites, indicating dynamic changes in the type of bonding.
To monitor covalent functionalization in a structure-specific manner, we develop a novel Raman spectroscopic method. We analyze the intermediate frequency mode (IFM) Raman features and their dependence on nanotube diameter and excitation wavelength. We establish the IFM-to-radial breathing mode (RBM) intensity ratio as a sensitive measure of defect density in SWCNT structures.
Using advanced molecular dynamics simulations, we study how ssDNA conformation influences guanine functionalization. Variables such as ionic strength, DNA to SWCNT mass ratio, and nanotube chirality impact the spatial distribution of guanine nucleobases on the SWCNT surface. These insights aid in tuning excitonic properties and designing SWCNT-based optoelectronic devices.
Our research also reveals that rose bengal (RB), a commonly used photosensitizer, forms charge transfer complexes with SWCNTs, crucial for guanine functionalization. Spectroscopic studies suggest that this interaction may facilitate the functionalization. We also discovered that RB interacts with nanotubes in a structure-specific manner, offering a method to monitor selective interactions between SWCNTs and their coatings.
Overall, this work provides new methods and insights for controlling and monitoring guanine functionalization of SWCNTs, with significant implications for developing SWCNT-based technologies in optoelectronics, photonics, and biomedical applications
1.6 Identifying intersections between BBCC and ecology and conservation
Get PDFDeveloped from the discussion at the “Identifying intersections between BBCC and ecology/conservation” working group as part of “Biotechnologies Beyond Conventional Containment (BBCC)” theme.This entreaty was created as part of The Spirit of Asilomar and the Future of Biotechnology summit (February 23-26, 2025) in Pacific Grove, CA.This Entreaty summarizes the key discussion points identified from a “Identifying intersections between BBCC and ecology/conservation” working group as one of the technical sessions under the “Biotechnologies Beyond Conventional Containment (BBCC)” theme at the Spirit of Asilomar and The future of Biotechnology summit. The session aimed to explore the intersection of biotechnology application in the environmental set-up for ecology and conservation purposes
The Role of Fittingness in Normative Theory
No full textOur mental life is characterized by a wide variety of attitudes. We admire, pity, or envy other people, we intend to act, and we desire certain things. Just as these attitudes can be appropriately directed, they can also be misdirected. Martin Luther King may warrant admiration, but a con artist does not. Some recent literature argues that there is a normative feature, fittingness, that governs which attitudes are properly directed towards which things. This dissertation considers the axiological, meta-ethical, and normative work that fittingness can do. Part 1 discusses the role of fittingness in a naturalist and realist meta-ethics. On my proposed naturalistic reduction, fittingness would be a sui generis correspondence relation between attitudes and entities. Other normative features, notably value, would be defined in terms of fittingness. This approach draws on Brentano’s analogy between fittingness and truth, insofar as truth is often considered to be a correspondence between propositions and states of affairs. I then show how my account can resist two kinds of error-theoretic arguments against normative realism.
Part 2, on normative explanation, defends a fittingness-based account of recognition respect. Darwall (1977) famously identified recognition respect as a form of respect that is owed to something in virtue of its status as a certain kind of thing, rather than because of its excellence or success. For example, persons may warrant respect simply because of their status as autonomous agents. So understood, recognition respect has long been influential in non-consequentialist theory. But recognition respect is seldom defined in detail. I argue that fittingness is the normative feature best-suited for defining recognition respect. The definition I defend is largely a reduction of recognition respect to fittingness; to show recognition respect for x is to take the attitudes (conative, evaluative, or both) that it’s fitting to take to-wards x, because of one’s recognition that these attitudes are fitting. Given such a fit-based definition of recognition respect, we can better explain why respect-based normative theories count as non-consequentialist. Additionally, appeals to fittingness allow the non-consequentialist to explain normative facts about obligation and permissibility.
Part 3, on axiology, defends a fittingness-based account of reasons. A key challenge is that while reasons are consequence-dependent and gradable, fittingness is typically considered to be both non-gradable and consequence-invariant. I review extant fit-based criteria that attempt to address this challenge. These criteria either yield unintuitive results or threat-en the role of fittingness in non-consequentialist explanation. In response, I defend novel fit-based accounts of both reasons and the weights of reasons. Together, these new criteria preserve the non-gradability and consequence-independence of fittingness, while explaining how reasons can be both gradable and consequence-dependent. As a result, given its meta-ethical, normative, and axiological roles, fittingness is a versatile feature that warrants a prominent place in our normative theorizing
Interactive AI Tutors for Training the Workforce of the Future
Get PDFThe need to train new workers effectively and upskill the existing workforce is a challenge faced by almost every industry across the globe. The healthcare industry, in particular, is confronting a crisis. The World Health Organization (WHO) projects a shortage of 10 million healthcare workers by 2030. However, according to the Future of Jobs Report by the World Economic Forum, only half of the workers have access to training and learning opportunities. To sustain a resilient workforce and to protect the health of the world’s population, my thesis looks at using AI and robots to
accelerate human learners’ acquisition of workforce skills. Specifically, I develop novel Explainable AI (XAI) algorithms to automate training to enable workers to collaborate with autonomous robots - a trend that is fast-growing. I also use statistical models to model human learner cognitive processes to create Human-Robot Interaction (HRI) systems to generate effective instructions tailored to individual learners. In addition to driving technical advances, my research is having a positive societal impact. I collaborate with Houston Methodist Hospital to create a first-of-its-kind robotic tutor for clinical nursing education to reduce healthcare-associated infections
ULTRAFAST PHONON DYNAMICS IN QUANTUM MATERIALS
No full textEngineering and controlling phonons in quantum materials has emerged as a versatile approach to tailor materials’ properties and drive novel physical phenomena. By prescribing large atomic displacements in crystalline lattices, phonon-driven emergent phases such as superconductivity, ferroelectricity and magnetism have been demonstrated. However, achieving such phononic control requires a thorough understanding of phonons including their lifetimes, coherence, and coupling to other quasiparticles. Optical spectroscopy is a powerful tool in this endeavor, offering deep insights into the fundamental properties of phonons while also enabling ultrafast dynamical control with unique selectivity and flexibility.
This thesis begins with a detailed investigation of the scattering mechanisms of optical phonons in boron arsenide (BAs) using high-resolution Raman and Fourier transform infrared (FTIR) spectroscopy. Our findings confirmed that the four-phonon scattering process dominates over the entire temperature range due to the large phase-scattering space for zone-center optical phonons in BAs. Moreover, we found that phonon-defect scattering is negligible compared to phonon-isotope scattering since the defect concentration of BAs is relatively lower than its isotope concentration. These results provide critical insights into the intrinsic and extrinsic scattering mechanisms of optical phonons in BAs, motivating further theoretical and experimental studies to understand anharmonic effects in this material.
To overcome the sensitivity and resolution limitation of conventional linear phonon spectroscopy, we developed novel nonlinear phonon spectroscopy techniques. Using time-resolved anti-Stokes Raman spectroscopy, we observed the ultrafast dynamics of linearly and circularly polarized E^' (Γ) phonons at the Brillouin zone center in single-crystalline monolayer WS2, which are excited by intense, resonant, and polarization-tunable terahertz pulses. We identified distinctive decoherence pathways by comparing the population lifetime, spatial coherence lifetime, depopulation lifetime, and chirality lifetime. Our results provide crucial information for improving the lifetime of chiral phonons in two-dimensional materials and potentially facilitate dynamic magnetic control of quantum materials.
Finally, we extended the probing capabilities by exploring terahertz electric field induced second harmonic generation (TEFISH), a third-order process that is allowed in all materials without symmetry requirements. We demonstrated time-resolved hyperspectral phase-sensitive heterodyne TEFISH microscopy in polymer thin films (SU-8), 2D crystalline semiconductors (MoS2), and sub-wavelength photonic resonators. By interfering the nonlinear emission with a local oscillator field, we quantitatively retrieved the frequency, amplitude, and relative phase of the χ^((3)) spectra. TEFISH microscopy allows time-resolved imaging of vibrational and photonic resonances with sub-wavelength resolution and higher sensitivity compared to linear infrared spectroscopy, as well as versatility for samples in different environments by avoiding near-field probes