OIST Institutional Repository
Not a member yet
2744 research outputs found
Sort by
Using Natural Analogues of the Future Ocean to Study the Adaptive Potential of Fish Communities to Environmental Change
Full text linkOkinawa Institute of Science and Technology Graduate UniversityDoctor of PhilosophyUnderstanding how fishes will respond to future ocean conditions under environmental changes can help us better understand the future of fish populations. Sites such as CO2 seeps act as natural analogues of the future ocean and can be used to understand the effects of ocean acidification (OA) on marine organisms. Examining fishes present at Natural analogues offer the opportunity to understand how they may be able to adapt to this environment. Our study used two natural analogues, a semi-enclosed bay in Bouraké, New Caledonia, and a CO2 seep off Shikine Island, Japan, to examine how the fishes found at these sites survive in this environment simulating an end-of-century scenario of OA. We examine the effects of OA on three levels: the community, the individuals, and the population. First, we examined how fish assemblages differed between the natural analogue and a nearby comparison site in Bouraké, New Caledonia. We used environmental DNA metabarcoding and underwater visual surveys to assess the fish assemblages at the two sites. Our study found that some species, such as gobies may be more tolerant of the multiple environmental stressors found in Bouraké compared to wrasses and parrotfish (Labriformes), which may be more sensitive to the effects of environmental change. Next, we examined the individual response to OA by sequencing the transcriptome of the brain and gill from the neon damselfish (Pomacentrus coelestis) at the CO2 seep off Shikine Island and a nearby control reef across two seasons to examine the genetic mechanism for adaptation. Our study found genes associated with acid-base regulation, O2 transportation, and immune responses were differentially expressed in response to conditions of OA found at the seep, supporting previous work examining the molecular mechanisms of adaptation OA in fishes. Finally, we examined the presence of selection for adaptation to OA at the CO2 seep off Shikine Island by collecting DNA from 135 P. coelestis across the island and examining genome-wide single-nucleotide polymorphism. We found potential genes under selection at the CO2 seep, suggesting selection for adaptation to OA. Our study shed light on the various effects of environmental change on fishes at natural analogues and the potential response of fishes to OA. However, there may also be adverse effects of OA, which warrant further investigation and highlight the importance of natural analogues to study how fishes respond to environmental changes
On the Representation Theory of Cyclotomic KLR Algebras
Full text linkOkinawa Institute of Science and Technology Graduate UniversityDoctor of PhilosophyIn this thesis, we study the representation theory of cyclotomic Khovanov–Lauda– Rouquier algebras, in particular, we consider homomorphisms between Specht modules in type A(1) ℓ and representation type in type Cℓ(1).
In the first part, using the presentation of Specht modules given by Kleschev, Mathas and Ram, we investigate homomorphisms into Specht modules labelled by hooks in quantum characteristic two. We give a complete description of the action of the generators on the basis elements of Sλ when λ is a hook. We use this result to identify a large family of partitions µ such that there exists at least one non-zero homomorphism from Sµ to Sλ, explicitly describe these maps and determine their grading. Finally, we generalise James’s well-known result for the trivial module.
In the second part, we investigate the representation type of cyclotomic KLR algebras of type Cℓ(1) for arbitrary levels. In level one, generalising Ariki and Park’s result for the fundamental weight Λ0, we determine the representation type for all Λk. For higher levels, we study a connected quiver consisting of all dominant maximal weights for an integrable highest weight module. Then, by using this quiver, we determine the representation type of cyclotomic KLR algebras for level two in type Cℓ(1)
The Role of Calcium Ion Dynamics and Inter-Organelle Communication During Plasma Membrane Damage-Dependent Cellular Senescence
Full text linkOkinawa Institute of Science and Technology Graduate UniversityDoctor of PhilosophyCellular senescence is a stable cell cycle arrest that contributes to a variety of physiological and pathological processes in vivo, including organismal aging, wound healing, and cancer. Accumulating evidence suggests that elimination of senescent cells ameliorates age-related pathologies. In vitro, various stresses, including oxidative stress, oncogene activation, telomere shortening, and DNA damage, induce cellular senescence via the DNA damage response. However, the triggers of cellular senescence in vivo remain controversial. Here, I show that cellular senescence is induced by physiologically and pathologically occurring plasma membrane damaging stimuli such as mechanical injury and pore-forming toxins in normal human fibroblasts in vitro. I found that Ca2+ influx into the cytosol following plasma membrane damage is necessary and sufficient for the induction of plasma membrane damage-dependent senescence. Live cell imaging revealed that Ca2+ entering the cytosol is immediately incorporated by the endoplasmic reticulum (ER). Subsequently, mitochondrial Ca2+ levels rise steadily, suggesting Ca2+ transport from the ER to the mitochondria via their contact sites. I observed an increase in mitochondrial oxidative stress, and attenuation of oxidative stress with antioxidants suppressed plasma membrane damage-dependent senescence. These results suggest that mitochondrial dysfunction due to Ca2+ accumulation induces plasma membrane damage-dependent senescence. I also found that Ca2+ transport from the ER to the mitochondria is necessary to maintain cytosolic Ca2+ levels and cell survival after plasma membrane damage. Proteomic analysis identified the proteins that mediate the ER-mitochondria contact. This study highlights an underappreciated subtype of cellular senescence, plasma membrane damage-dependent senescence, and provides mechanistic insights into Ca2+ dynamics based on plasma membrane damage-triggered inter-organelle communication
Characterisation of Serotonin, Noradrenaline and Dopamine Release in the Motor Cortex
Full text linkOkinawa Institute of Science and Technology Graduate UniversityDoctor of PhilosophyThe precise spatiotemporal dynamics of neuromodulator release in the cortex remain elusive. These release patterns determine receptor activation, as receptors with different affinities are activated by different concentrations, and thereby distances, from the release site. While neuromodulator nuclei have been extensively characterised, technological challenges have hindered detailed cortical investigation. This thesis clarifies the release patterns of dopamine, noradrenaline, and serotonin in the secondary motor cortex (M2) using a novel orthogonalized Go/NoGo task developed for head-fixed mice. We dissect neuromodulator activity at the intersection of locomotion and unconditioned stimuli (US). Employing two photon microscopy and novel genetically encoded sensors, we achieved high-resolution imaging unattainable with previous techniques. Our findings indicate that serotonin, noradrenaline, and dopamine are robustly correlated with locomotion transitions, exhibiting significant increases from rest to locomotion and decreases during the reverse. Cross-correlation analysis suggests neuromodulator activity precedes locomotion onset, potentially facilitating motor behaviours. Unexpectedly, both appetitive (sucrose) and aversive (air-puff) stimuli elicited fluorescence decreases in all neuromodulators. Serotonin and noradrenaline showed stronger, more consistent responses during movement than rest, while dopamine responses were more consistent across locomotion states. Detailed analysis of activity maxima and minima within individual trials revealed significant variability and complexity. Contrary to expectations, no neuromodulator responses to US-predicting cues were observed, despite anticipatory behavioural changes. This highlights the need for further investigation into sensory cue processing in M2. Our findings suggest a complex multiplexing of information in M2, whereby neuromodulator activity is more influenced by locomotive state than appetitive or aversive stimuli delivery
Fabrication and Spectroscopic Investigation of a Tunable Magnetic Material and its Heterostructures
Full text linkOkinawa Institute of Science and Technology Graduate UniversityDoctor of PhilosophyThe interplay between magnetism and the spin polarized surface states of topological insulators (TIs) can open a gap and give rise to the emergence of exotic states. Such states can be realized by the selective engineering of a magnetic material (MM)/TI heterostructure, inducing magnetic ordering via proximity effects. For this purpose, a tunable layered MM, Cr1+δTe2, is fabricated and investigated in this thesis. A method to systematically control the δ content in molecular beam epitaxy grown thin films is developed. The effect of the δ content on the band structure is visualized by angle-resolved photoemission spectroscopy, revealing a rigid-band-like shift and the resulting tunable Hall properties. The magnetic properties are characterized, revealing the switch of the magnetic anisotropy with δ, explained by the increasing interlayer exchange interactions. To conclude, Cr1.33Te2/Bi2Te3 heterostructures are fabricated and local variations on the magnetic proximity effect are investigated in real space, combining scanning tunneling microscopy/spectroscopy and cross-sectional transmission electron microscopy experiments. A correlation between a spatially inhomogeneous gap opening and distinct Bi2Te3 thicknesses is hypothesized. This thesis provides a universal insight into the direct exploration of quantum phenomena in magnetic TI heterostructures
Planetary Systems Insights through Numerical Data Imputation Algorithms and Machine Learning
Full text linkOkinawa Institute of Science and Technology Graduate UniversityDoctor of PhilosophySince the first discoveries in the early 1990’s, the number of known exoplanets has exploded to reach over 5,500 as of December 2023. But the recorded information for each planets is sparse, with a lot of missing values, preventing from confidently drawing overarching conclusions. As most traditional data imputation methods provide a point estimate, they fail at capturing the complexity of multimodal data distributions and provide unreliable estimates in scenarios where data exhibits multiple modes. This calls for a new paradigm to model rich or complex numerical datasets.
This PhD thesis introduces the kNN×KDE, a numerical imputation tool which combines the flexibility of the k-nearest neighbors (kNN) and the simplicity of Kernel Density Estimation (KDE) to model the multi-dimensional distribution of missing data in datasets characterized by multimodality. This new method is tested against traditional and novel data imputation algorithms, and I show that the kNN×KDE not only provides better estimates, but also facilitates their interpretation.
To demonstrate the practical significance of the kNN×KDE, I apply it to the NASA Exoplanet Archive – a dataset riddled with missing values, including both planetary radius and mass, and marked by pronounced multimodality. The analysis of the estimated distributions provided relevant insights into the demographics of the Exoplanet Population, potentially helping future missions to select interesting targets.
In addition, this PhD work includes two artificial neural network applications for planetary system analysis: a Convolutional Neural Network (CNN) to predict planetary system stability and a Graph Neural Network (GNN) to rediscover Newton’s Law of Gravitation and attempt to reproduce the scientific discovery of Neptune. Finally, this thesis features a Transformer model for Symbolic Regression applied to 120 real-world physics equations. These additional tools contribute to further characterize planetary systems evolution and understand the limits of Machine Learning for scientific discovery
Design, Fabrication, and Characterization of Optical Nanofiber Cavities
Full text linkOkinawa Institute of Science and Technology Graduate UniversityDoctor of PhilosophyOptical nanofibers (ONFs) pave the way for researchers to understand and control light-matter interactions at the nanoscale. Evanescent light fields at the waist of ONFs can be coupled to quantum emitters for various studies. In particular, significant experimental progress on quantum emitter coupling with an ONF-based cavity mode, for cavity quantum electrodynamics (cQED), has been achieved in the last two decades. This thesis showcases the following topics: (i) the development of novel ONF cavity fabrication methods using a focused ion beam (FIB) which provides highly reflective cavity mirrors with more stable fabrication quality than conventional fabrication methods, (ii) the optical characterization of ONF cavities fabricated using the FIB technique, (iii) the investigation of the effects of laser annealing on the cavity modes, and (iv) the realization and characterization of an ONF-based cavity supporting higher-order modes (HOMs) and controlled excitation of the desired HOMs with polarization topology. This is a significant step toward degenerate multimode cQED and potential access to evanescent field singular optics using a HOM-ONF. This PhD work advances ONF-based cavity systems, not only for cQED studies but also contributes to their fundamental understanding in quantum optics, structured light, and beyond
Synthesis and Reactivity of Transition Metal Complexes Supported by Non-Phosphine Ligands in Metal-Ligand Cooperation and Fluoroalkyl Incorporation
Full text linkOkinawa Institute of Science and Technology Graduate UniversityDoctor of PhilosophyThe thesis describes the synthesis and reactivity of metal complexes supported by nonphosphine ligands in metal-ligand cooperation and fluoroalkyl incorporation. The first chapter introduces the literature review on metal-ligand cooperation as a tool for bond activation and catalysis, and the synthesis of manganese(I) and ruthenium(II) complexes supported by non-phosphine N,S-donor macrocyclic pyridinophane ligands. These complexes undergo a facile, reversible single and double dearomatization in pyridine rings in the presence of the base. In the second chapter, we continue utilizing the macrocyclic pyridinophane scaffolds for the synthesis of high-valent manganese(III) complexes via oxidative addition of aryl bromide to manganese(I) precursor and study Ar-Br reductive elimination via one-electron oxidation. We also present the new synthetic route to cyclometalated high-valent manganese(III) fluoro complexes using a trifluoromethylating reagent via transmetalation followed by α-fluorine elimination, resulting in the release of a difluorocarbene. That facile generation of a difluorocarbene could be utilized in difluorocarbenation of alkenes and alkynes using Zn trifluoromethyl reagent at lower temperatures and shorter time as compared to a manganese-free reaction. The third chapter includes literature review on radical fluoroalkylation mediated by first-row transition metal complex, then focusing on the synthesis of cobalt perfluoroethyl complexes supported by simple N-donor naphthyridine ligands. These complexes showed Co-C2F5 bond homolysis under visible-light irradiation and could be utilized as catalysts for light-induced C-H bond perfluoroalkylation in arenes using Togni reagent
Investigation of the Sense of Agency in Human–Robot Interaction Based on the Free Energy Principle
Full text linkOkinawa Institute of Science and Technology Graduate UniversityDoctor of PhilosophyThe thesis study aims to enhance understanding of social interaction mechanisms by investigating the sense of agency (SoA) through the lens of the free energy principle (FEP). For this purpose, a novel model is proposed, which is evaluated by conducting human–robot interaction experiments with human subjects. While humans engage in various forms of social interaction, ranging from cooperation to conflict, the underlying mechanisms shaping these dynamics remain elusive. By focusing on SoA, which denotes the subjective sensation of control over one’s actions, the study attempts to elucidate its relationship with social interaction dynamics. We employ the free energy principle (FEP), a prominent theory in neuroscience, as the theoretical underpinning of the study. The FEP posits that the brain executes various functions, such as perception and action generation, by minimizing a statistical quantity known as free energy. This quantity comprises two terms: the complexity term, which emphasizes top-down processing rooted in prior learning, and the accuracy term, which prioritizes bottom-up processing based on observation. Consequently, free energy minimization entails a dynamic interplay between top-down and bottom-up information processing in perception and action generation.
Although prior research on the FEP using artificial neural networks has explored the complexity-accuracy balance during the training phase, there is a dearth of investigation into how altering this balance during the testing phase impacts network behaviors. Given individuals’ propensity to exhibit varying behaviors in different contexts, we hypothesize that adjusting the balance between top-down and bottom-up processes during the interaction influences behavioral outcomes, thereby affecting the strength of SoA. To test this hypothesis, we propose a novel multimodal computational model for visual and proprioceptive perception based on the FEP, employing a variational Bayes recurrent neural network. We design a task involving mutual imitative interaction between a human and a robot and conduct both simulation and physical experiments.
Our findings demonstrate that modifying the complexity–accuracy balance during interaction modulates the strength of SoA in human-robot interaction. When the prioritization of minimizing the complexity term is heightened, the robot exhibits more egocentric behavior, exerting greater influence on the human, thus indicating a stronger SoA. Conversely, when this prioritization is reduced, the robot displays a tendency to adjust its intentions to align with those of the human, suggesting a weaker SoA. By proposing a computational model and analytical methodologies grounded in the FEP and validating them through human-robot interaction experiments, this thesis offers insights into the mechanisms underlying diverse social interaction dynamics from the perspective of SoA
Ultracold Atoms: Applications in Metrology and Fundamental Properties of Quantum Droplets
Full text linkOkinawa Institute of Science and Technology Graduate UniversityDoctor of PhilosophyIn the past decades, cold atoms have been indispensable tools in the study of fundamental physics and its application to quantum technologies. Due to the high degree of controllability they can be used to investigate systems over wide ranges of parameter regimes and, as will be important in my thesis, not only in three dimensions but also in lower dimensions, and in equilibrium and out-of-equilibrium. In particular, I explore this vast landscape primarily through my work on two topics involving quantum metrology and quantum mixtures. In the first topic, I study how a Floquet-engineered bosonic system in a one dimensional lattice can be utilized as a platform for quantum metrology. In particular, I focus on determining how the quantum Fisher information, a quantity that is related to the lower bound of precision measurement, can be optimized in this setup, and then discuss other strategies that are realizable in an experimental setup. The second topic focuses on quantum mixtures involving a relatively new phase of matter called quantum droplets, where I study the effects of introducing impurities in one case and the dependence on dimensionality in the other. In the second project, I show that the introduction of fermionic impurities to the droplet leads to noticeable deviations in the ground state and dynamical properties as the interactions between droplet and fermions is increased and, in the same manner, the fermionic properties are also altered with clear signatures in the density. In the third project, I show that characterizing the droplet as 2D or quasi-2D heavily relies on the mean-field interactions as well as the transversal trapping strength. In regions where the 2D and quasi-2D descriptions are comparable, however, differences in the observed ground state and dynamical properties still arise as different LHY corrections are valid in different descriptions