12023 research outputs found
Sort by
Variable-Stiffness and Shape-Morphing Structured Media
Get PDFAdvancements in additive manufacturing and material synthesis with highly controlled geometries have enabled the creation of structured media, engineered materials with patterned micro- and meso-scale geometries that impart unique mechanical properties. By fine-tuning these architectures, structured materials can achieve properties beyond those of their base materials. A subcategory, structured fabrics, consists of discrete granular particles rather than continuous fibers. Their mechanical behavior is governed by jamming, a transition driven by geometric constraints, allowing them to switch between flexible and rigid states. By leveraging the interactions of the building blocks, structured fabrics enable tunable stiffness, global shape change, and adaptive functionalities, making them ideal for wearable, deployable, and morphing structures.
The first structured fabric study explores a topologically interlocking material (TIM) system with adjustable bending stiffness controlled by external pre-stress. The system consists of truncated tetrahedral particles connected by tensioned nylon wires, allowing stiffness to be tuned by varying wire tension. Experiments examine the effects of surface friction and interlocking angle on bending response, guided by Level Set Discrete Element Method (LS-DEM) simulations. The second design presents deployable 3D structures that fold without rigid mechanisms, offering compact storage and stable deployment. The design consists of computationally generated rigid tiles adhered to a pre-stretched elastic sheet, which transforms from a flat state and jams into a predetermined 3D shape when released. Although the designs exhibited unique mechanical properties, experimentally understanding their internal mechanics was challenging due to limited visibility of the concealed membrane upon jamming. To optimize future designs, simulations were conducted to analyze the effects of various pattern designs and folding on membrane behavior.</p
SpLacZ-MERCS-Coupled CRISPRi Screening Identifies Novel Mitochondria-ER Contact Sites Regulators
Get PDFMitochondria-ER contact sites (MERCS) mark critical hotspots for a variety of cellular processes, including calcium homeostasis, lipid homeostasis, mitochondria dynamics, and quality control. Fluorescence-based tools have been the main approach to detect MERCS, with a large portion of studies using split fluorescent proteins, which assemble at sites of contact to yield a fluorescence signal. However, they have limitations, including little to no response to fluctuations in MERCS abundance, low sensitivity, and possible artifacts made due to reporter protein reconstitution. To overcome this, we developed the SpLacZ-MERCS sensor, the first MERCS reporter using split β-galactosidase (LacZ). Compared to using complementary GFP fragments that go to mitochondria and ER, SpLacZ-MERCS gives an integrated readout of MERCS activity for more accurate and quantitative monitoring of these contact sites in single cells over time. Our system has specific organelle targeting but does not induce artificial tethering, which allows it to be a standard tool for studying MERC dynamics in physiological and pathological conditions. Using pharmacological and genetic perturbations known to modulate mitochondria–ER interactions, we validated SpLacZ-MERCS as an effective and reliable sensor of MERCS abundance.
Beyond tool development, we sought to uncover the molecular mechanisms regulating MERCS using a genome-wide CRISPR interference (CRISPRi) screen combined with SpLacZ-MERCS. This unbiased approach led to the identification of RHOA, a small GTPase known for its roles in cytoskeletal dynamics and signal transduction as a novel regulator of MERCS. We found that RHOA directly interacts with the ER-resident protein VAPB and modulates its binding to PTPIP51, a mitochondrial protein involved in forming MERCS junctions. VAPB and PTPIP51 constitute a MERCS tethering complex. RHOA depletion or overexpression of CUL3 (which promotes RHOA degradation) results in reduced MERCS levels, while RHOA overexpression enhances MERCS formation. Notably, we discovered that disease-associated mutations in RHOA, CUL3, and VAPB—implicated in cancer, metabolic disorders, and neurodegeneration—disrupt MERCS regulation, suggesting a potential link between MERCS dysfunction and disease pathology.
Together, our study makes two significant contributions. SpLacZ-MERCS is a new signal-integrating MERCS reporter system that allows dynamic, cumulative tracking of mitochondria-ER interactions. RHOA has been established as a novel regulator of MERCS, providing a framework to understand how contact sites can be manipulated in a dynamic way upon cellular signals. These findings enhance the foundation of our understanding of MERCS regulation while also shedding light on new possible therapeutic targets for diseases associated with altered communication between mitochondria and the ER.</p
Sums of Various Dilates
No full textGiven a finite subset A of an ambient abelian group and a dilate λ, how large must the sum of dilate A+λ∙A be in terms of A? In this thesis, we study this problem in various settings and generalizations, proving tight bounds in many cases. Our five main results are as follows.
1. In the setting of a d-dimensional subset A of ℝᵈ, we prove an exact lower bound on the size of the difference set A-A.
2. In the case when λ ∈ \in C is a transcendental number, we show that there is an absolute constant c>0 such that |A+λ∙A|≥
exp(c√log|A|)|A| for any finite subset A of C. This is best possible up to the constant c.
3. In the algebraic case, given algebraic numbers λ1,...,λk, we prove tight lower bounds for the sum of dilates A+λ∙A+ ... λk∙A. As an important ingredient, we also prove a Freiman-type structure theorem for sets with small sums of dilates.
4. In the setting of sums of linear transformations, we prove tight bounds for the sum of two linear transformations and tight bounds for the sum of multiple pre-commuting linear transformations.
5. In the setting of groups of prime order, we prove near-optimal lower and upper bounds for the sum of dilate A+λ∙A for A of a given density and large λ.</p
New Technologies for Control and Measurement of Polyatomic Molecules
Get PDFThe Standard Model of particle physics has tremendous explanatory power, and while cosmological evidence assures us that it is incomplete, we have never observed a convincing signature of its violation in a laboratory setting. Extensions of the Standard Model proposed to solve one or more of the theory's open questions generically allow for violation of fundamental, discrete symmetries such as CP symmetry, and cosmological processes such as baryogenesis point to CP violation as a fundamental ingredient of our cosmos. Searches for a permanent electric dipole moment (EDM) of the electron inside polar molecules are sensitive probes of new CP violating physics, and these experiments have constrained new CP violating physics to beyond energy scales that are directly accessed at the Large Hadron Collider. EDM experiments with polar molecules are typically limited in sensitivity by either molecule number or coherence time. An electron EDM experiment in ultracold, trapped polyatomic molecules promises to extend the new physics reach by many orders of magnitude, but there are a number of major technical challenges with these experiments, including molecular beam deceleration and high-resolution spectroscopy of cold, free radicals. This thesis reports the development of new technologies and methods for control and measurement of polyatomic molecules in support of next-generation EDM measurements
Predictions and Policy Optimization in Online Decision Making
Get PDFPredictions are ubiquitous in modern systems, offering insights into how environments might evolve by encoding our prior knowledge and assumptions. Recent advances in artificial intelligence have significantly expanded the scope and accuracy of such models, creating vast new opportunities across domains. At the same time, online decision making remains a fundamental challenge in many real-world problems, concerned with challenges such as limited information, delayed feedback, and irrevocable actions. This dissertation focuses on the interplay between predictions and online decision making---how predictive information can be effectively leveraged to improve performance in dynamic, uncertain environments.
While incorporating predictions often enhances decision-making, the degree of improvement can vary substantially. This variability arises from two key factors. First, the potential benefit of using predictions is fundamentally determined by both the nature of the predictions (e.g., their targets, errors, and distributions) and the characteristics of the decision-making process (e.g., costs and dynamics). Second, standard predictive policies frequently fall short of realizing such potential, especially in changing environments or when critical system parameters are unknown.
This dissertation introduces a unified theoretical framework to quantify the benefit of leveraging predictions across a broad range of online decision-making problems. To close the gap between the maximum potential and achievable performance, we formulate a general policy optimization framework and design efficient algorithms capable of tracking optimal (predictive) policies in time-varying settings. Additionally, we address practical considerations such as scalability and computational efficiency, enabling the application of our methods in large-scale networks and on resource-constrained devices.</p
Beyond Symmetry: Normality-Based Analysis of Velocity Gradients in Turbulent Flows
No full textSmall-scale turbulence is a hallmark of countless natural and engineered flows. Its features are often described and modeled using the velocity gradient tensor (VGT), which is conventionally decomposed into the (symmetric) strain-rate tensor and the (antisymmetric) vorticity tensor. Although this symmetry-based decomposition has found use in areas such as vortex identification and closure modeling, it provides limited insight into local flow structure. A more refined description can be obtained by further distinguishing the normal and non-normal parts of the VGT. The resulting normality-based decomposition identifies contributions associated with normal straining (symmetric/normal), rigid rotation (antisymmetric/normal), and pure shearing (non-normal). We use this decomposition to identify flow features that are obscured by symmetry-based analyses yet have significant implications for efforts to understand and model turbulent flows.
We first demonstrate that partitioning the strength of velocity gradients using our normality-based approach can distinguish between different regimes in various turbulent flows. In wall-bounded flows, the near-wall partitioning is dominated by shearing whereas the partitioning far from the wall collapses onto the partitioning associated with isotropic turbulence. In an unbounded vortex ring collision, our analysis distinguishes the initial vortex rings, which have a strong imprint from rigid rotation, from the decaying turbulent cloud produced by their collision, for which the partitioning is similar to that of isotropic turbulence. It also identifies enhanced shear–rotation correlations as a distinctive fingerprint of the elliptic instability during transition, which can be interpreted using relevant geometric features of local streamlines. By deriving algebraic expressions for the partitioning constituents in terms of the invariants of the VGT and an additional parameter, which represents the alignment of shear vorticity with the local rotation axis, we identify a key facet of our analysis that goes beyond previous analyses of the VGT.
We then apply our normality-based framework to filtered velocity gradients in direct and large-eddy simulations of isotropic turbulence. Our analysis enables shear layers, which are associated with shear vorticity, to be distinguished from vortex cores, which are associated with rigid rotation, in a multiscale setting. It reveals that filtering mitigates the relative contribution of shear layers in the subinertial range of the energy cascade. Moreover, it identifies crucial (yet perhaps overlooked) contributions from shear layers to fundamental energy transfer mechanisms, including strain self-amplification, vortex stretching, and backscatter associated with strain–vorticity covariance. The dominant role of shear layers in the backscatter mechanism suggests that they contribute significantly to the bottleneck effect in the subinertial range of the cascade. Our analysis of large-eddy simulation data shows that they also amplify the artificial bottleneck effect produced by an eddy viscosity model in the inertial range. This reflects that the eddy viscosity model mimics an unfiltered direct numerical simulation at a lower Reynolds number. A mixed model can be used to mitigate the artificial bottleneck effect since it more accurately mimics a filtered direct numerical simulation.</p
Compact Object Binaries in the Multiwavelength and Time Domain Sky
No full textCompact objects are natural laboratories to study the most extreme physics under conditions unable to be replicated anywhere on Earth. White dwarfs (WDs) are the most abundant compact objects, and when located in binaries, it becomes possible to measure physical properties such as mass and density. Remarkable phenomena result from interacting WD binaries; for instance, Type Ia supernovae, which established the existence of dark energy, likely result from the coalescence of two WDs or the accretion of matter by a WD in a binary.
This thesis focuses primarily on interacting WD binaries, in the form of cataclysmic variables (CVs) and their ultracompact cousins, AM CVns. The main product of this thesis is the deepest X-ray survey of CVs and AM CVns to date, assembled using a multiwavelength crossmatch of the SRG/eROSITA all-sky X-ray catalog, \textit{Gaia}, and time-domain photometry from the Zwicky Transient Facility (ZTF). I present a rejuvenated version of a tool used for the discovery of such systems in the X-ray + optical sky that would be missed in purely optical surveys. I calculated CV and AM CVn space densities and luminosity functions, and showed that 1) observations indeed reveal a dearth of accreting WDs compared to population synthesis predictions, and 2) the mean X-ray luminosity of CVs was overestimated by a factor of 10--100 in the past.
Along the way, several single-object papers shine a new light on the diverse physics of binary star evolution. I report the discovery of the second-nearest eclipsing AM CVn and, by constraining binary parameters, show that the "evolved CV" formation channel, which only involves one episode of common envelope evolution, is most likely. I include work on multiwavelength follow-up of the nearest black holes to Earth, Gaia BH1 and BH2, and show that the the lack of a detection confirms predictions of hot accretion flows in the extreme sub-Eddington regime. Later, I present a multi-year, multiwavelength campaign of an enigmatic accreting WD, and argue that it is a missing link between rapidly spinning WD pulsars and slowly rotating polars. This object serves as strong evidence for the dynamo theory of WD magnetism in CVs, where a WD must be spun up by accretion to generate a strong magnetic field. Finally, I report optical spectroscopy of a new radio source pulsing on a 2.9-hr timescale, the slowest at the time of publication. I show that this is a WD + M dwarf binary with a particularly massive (~ M☉) WD, likely representing a new subclass of long period radio transients.</p
Error Quantification and Mitigation for Numerical Compact Binary Waveforms
No full textGravitational wave analysis requires waveform models to compare with observed signals from compact binaries. These models are based on and validated by numerical relativity waveforms---waveforms output from codes developed to numerically evolve the Einstein field equations. The efficacy of numerical waveforms for analysis is limited by error from both numerical and astrophysical sources. This thesis makes two contributions to the quantification and mitigation of this error.
Chapter 2 describes a new algorithm for eccentricity reduction, the process of determining initial conditions for quasicircular binary orbits. This iterative procedure requires a measurement of eccentricity based on an early-inspiral trajectory. We find that the use of nonlinear fitting techniques such as variable projection leads to vastly improved consistency in eccentricity measurements.
Finally, Chapter 3 presents an in-depth quantification of error in numerical binary neutron star waveforms from three vastly different numerical relativity codes. We find that overall these codes produce consistent binary neutron star evolutions, but that further accuracy improvements will be required for analysis of next-generation gravitational wave detector signals.</p
Understanding Cessation of Neural Crest Migration and Onset of Gangliogenesis
Get PDFThe neural crest is a multipotent, vertebrate-specific embryonic cell population that originates at the border of the developing central nervous system. Often referred to as the "fourth germ layer," the neural crest gives rise to diverse cell types, including craniofacial structures and components of the peripheral nervous system. Neural crest cells from specific axial levels in the embryo generate unique sets of progeny and migrate along distinct pathways, differing from those at other axial levels. During development, the formation of key structures within the vertebrate head, such as cranial ganglia and sense organs, requires coordinated migration and interactions between two distinct embryonic cell populations: the neural crest and the ectodermal placodes. The dual embryonic origin of cranial sensory ganglia has interested investigators for some time, yet surprisingly, little is still known about the neural crest–placode relationship. Despite extensive research, the process of cranial gangliogenesis, an intriguing example of how cell–cell interactions drive the assembly of complex structures in the developing embryo, remains incompletely understood. To address this gap, I aimed to advance our understanding of neural crest contributions to cranial sensory ganglia formation and investigate how interactions between these two distinct cell populations contribute to chick trigeminal gangliogenesis.
To investigate this process, I focused on the early formation of the trigeminal ganglion, emphasizing on the transcriptional regulation of neural crest-derived cells. Using a combination of lineage labeling and in situ hybridization in chick embryos, we demonstrated that the transcription factor Tlx3 is expressed in neural crest-derived cells contributing to the cranial trigeminal ganglion, coinciding with the onset of ganglion condensation. Notably, loss-of-function experiments revealed that Tlx3 deficiency results in smaller ganglia with fewer neurons. Conversely, ectopic expression in migrating cranial neural crest cells accelerates neuronal differentiation, underscoring its critical role in neural crest-derived neuronal development. Taken together, these results demonstrate a pivotal role for Tlx3 in neural crest-derived cells during chick trigeminal gangliogenesis.
As an additional candidate mediator, I investigated the potential role of Cxcl14. The concurrent expression of CXCL14 in placodal cells and its potential cognate receptor CXCR4 in neural crest cells raised the intriguing possibility that this ligand–receptor pair mediates signaling from placodal to neural crest cells, representing an additional form of their cell-cell interactions. Loss of Cxcl14 disrupts gangliogenesis and axonal projections, revealing an essential role for this chemokine in guiding neural crest-placode interactions during early ganglion formation. More specifically, perturbing Cxcl14 in the placodal population resulted in increased dispersion of neural crest-derived cells in the maxillomandibular lobe but not in the ophthalmic lobe of the trigeminal ganglion, highlighting its critical role in directing neural crest-placode interactions during early ganglion formation.
In summary, the findings from my thesis advance our understanding of neural crest contributions to cranial sensory ganglia formation. By elucidating transcriptional and signaling mechanisms involved in trigeminal gangliogenesis, these results provide key insights into vertebrate neurodevelopment and lay the groundwork for further studies into neural crest biology
Numerical Modeling of High-energy Transients from Black Holes and Neutron Stars
Get PDFAlong with recent breakthroughs in relativistic astrophysics and multi-messenger astronomy, theoretical studies on compact objects and the dynamics of relativistic matter surrounding them have a growing significance. General relativistic approaches are required to properly describe astrophysical phenomena taking place in a strong gravity regime, yet the high complexity and nonlinearity of the equations governing those systems compel numerical approaches. In this thesis, we develop a computational method for and present global numerical simulations of relativistic plasma around compact objects, particularly focusing on high-energy electromagnetic transients originating from black holes and neutron stars. Our works include a new hybrid numerical scheme for modeling force-free magnetospheres of compact objects, large-scale simulations of a spinning black hole immersed in a magnetized wind, and magnetospheric transients from a merging black hole--neutron star binary