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The Illusion of Time in Physical Performance: Manipulating Timing Cues to Improve Plank Endurance in Trained Adults
No full textBackground: Deceptive timing feedback has been shown to enhance performance in endurance tasks, though its applicability to isometric exercises and interactions with approach motivation remains unclear. This study explores whether manipulated timing cues influence plank endurance and the role of motivation in these effects.
Methods: Fifty-seven active adults (63.1% male) participated in three maximal effort plank holds under different timing conditions: (1) accurate, (2) slowed, and (3) accelerated timing cues. Plank endurance was the primary outcome. Participants also completed the Approach-Avoidance System Questionnaire (AASQ) and the International Physical Activity Questionnaire - Long Form (IPAQ-LF) to assess motivation and fitness levels. Perceived exertion was evaluated using the Borg CR-10 RPE Scale.
Results: Timing cues significantly influenced plank endurance, with participants holding planks significantly longer in the slowed condition compared to the accelerated condition (p .001). Descriptive improvements in plank endurance from accurate to slowed conditions were not significant (p = .073). RPE did not significantly differ across conditions, indicating that performance gains were achieved without increased subjective effort. Motivation did not moderate the relationship between timing cues and endurance.
Conclusions: These findings suggest that altering time perception can influence endurance without affecting perceived exertion, though future research should explore whether different exercise modalities or greater variations in approach-oriented motivation may produce stronger effects.Extension Studie
Design Tool Used for the Selection of Nanoparticle Drug Delivery Systems in the Treatment of Respiratory Diseases
No full textThis goal of this study was to identify nanoparticle (NP)-related drug delivery systems that could be used for the treatment of respiratory diseases; and to develop a design tool that could be used to create new NP drug delivery systems for the treatment of a variety of respiratory diseases. As a large number of moderate to severe respiratory diseases remain incurable, with available therapeutic options only offering a temporary relief of symptoms; this design tool could potentially assist in the development of new pharmacotherapeutics that could curb and cure even the most severe and life-threatening of respiratory diseases. In order to create this design tool, a large sample of research publications were screened for references to respiratory diseases and medical treatment using nanoparticles. A few scenarios and assumptions were created, based on information from the sample of research publications and other publicly available information. As this was the initial development stage of the design tool, only a few scenarios and assumptions were tested. Theoretically, a software design tool would enable the faster and easier testing of various combinations of NPs, and facilitate the rapid development of efficacious treatment for moderate to severe respiratory diseases. The output from the design tool could also be further tested and validated using in-vitro and in-vivo systems. While the initial focus of the design tool was the identification of new NP treatment options for a selection of respiratory diseases; the tool could also potentially be modified to treat other respiratory diseases and other tissue and organ system diseases as well.Extension Studie
Endothelial Gap Junctions in the Control of Neurovascular Coupling
No full textThe brain depends on a highly regulated blood supply to power the energetically expensive computations that underlie cognition. To ensure that energetic resources are efficiently allocated, the brain dynamically redistributes blood flow to active regions via a process known as neurovascular coupling. This close matching of neural activity and hemodynamics is thought to be essential for neuronal homeostasis and forms the basis of non-invasive functional brain imaging in humans. That said, the molecular mechanisms underlying neurovascular coupling remain poorly understood.
To generate robust changes in local perfusion, neurovascular coupling involves the rapid, coordinated dilation of large stretches of the brain’s arterial network. The goal of this dissertation is to understand how this finely tuned, moment-to-moment matching of neuronal and vascular systems is achieved. Specifically, we demonstrate that endothelial gap junction-mediated signaling serves as an intermediary linking neuronal activation to long-range mobilization of the arterial network.
Leveraging a novel, endothelial-specific adeno-associated virus variant, we develop a non-invasive methodology to assay gap junction coupling in vivo. Using this technique, we find that endothelial cells throughout the central nervous system are functionally interconnected by gap junctions. Furthermore, we find that both the strength of this coupling and the specific connexin isoforms used by endothelial cells to form gap junctions vary along the arterio-venous axis. Based on these results, we generate a conditional loss-of-function mouse model to acutely abolish arterial endothelial cell gap junction coupling in the cerebrovasculature. Finally, using a combination of visual and optogenetic stimuli presented to awake mice, we show that endothelial gap junction coupling is essential for rapid, long-range propagation of vasodilation during neurovascular coupling.Medical Science
The Peso Perspective: Understanding Risk and Return in Global Currency Markets
No full textThe drivers of currency excess returns remain poorly understood despite the foreign exchange market’s size and liquidity. Using five measures of risk — novel text-based measures (from newspaper articles and firm earnings calls) alongside traditional risk indices that capture a country’s economic, financial, and political risk — I show that financial risk is the dominant predictor of volatility in emerging market currency returns, while geopolitical risk is positively associated with excess returns, supporting a risk premium explanation for the profitability of currency trades. Firm-level risk perceptions, especially from foreign firms, outperform political/economic risk in forecasting returns. However, country-specific risks explain only a fraction of exchange rate movements, revealing fundamental limits to forecasting exchange rate movements. The results highlight financial stability as a stronger determinant of risk premia than political uncertainty, with implications for currency speculators and policy-making in emerging economies.Applied Mathematic
Teeth and Dental Development as a Peripheral Marker of Early Life Stress Exposure in Mice
No full textIntroduction: Early life stress (ELS) has been shown to have long-lasting effects on human and murine development. In humans, ELS has been shown to increase the risk of anxiety, depression, and substance abuse later on in life. In mice, ELS in the form of limited nesting and bedding material has been shown to have persistent effects on adult murine behavior, with more persistent effects observed in males. Compared to females, males show an accelerated development of fear conditioning and significant depression and anxiety-like behavior. Conversely, females show delayed sexual maturation and cognitive function; these manifestations seemingly resolve with age.
Objectives: We asked whether dental development tracks the deviations in development and allows for the use of teeth as a potential biomarker of early life adversity. We tested whether the expression of receptors that link neural development with dental development can be used as mechanistic markers of altered tooth mineralization.
Material and Methods: Eighty-seven C57BL/6J mice from ELS and control groups were sacrificed at postnatal days 12 (n=49) and 78-83 (n=38). Whole heads were fixed in 10% zinc-formalin and, after rinsing, stored in 50% ethanol. To analyze craniofacial and dental development, whole heads and mandibles were scanned at 6 μm voxel size (Scanco μCT-40). Image stacks were analyzed using ImageJ, Imaris, and Amira software. For immunohistochemistry (IHC) and immunofluorescence (IF) procedures, soft tissue was removed, and fixed mandibles were dehydrated, embedded in paraffin, and sectioned. Kallikrein-related peptidase 4 (KLK4), androgen receptor (AR), and gamma-aminobutyric acid alpha one (GABA-α1) receptor expression were evaluated. Primary antibodies used were: rabbit polyclonal anti-GABA A receptor alpha 1 antibody, rabbit monoclonal recombinant anti-androgen receptor antibody, and rabbit polyclonal anti-KLK4 receptor antibody. Secondary antibodies used for IHC and IF, respectively, were biotinylated goat anti-rabbit IgG and goat anti-rabbit Alexa Fluor 594.
For elemental maps of mature, erupted enamel and dentin, fixed mandibles were embedded in Epo-Tek 301-1 epoxy resin and polished to the sagittal midplane of the incisor. Laser ablation-inductively coupled mass spectrometry (LA-ICP-MS) analysis was performed. Semi-quantitative analyses of sodium, potassium, magnesium, phosphorous, sulfur, chloride, iron, nitrogen, and carbon normalized to calcium were performed using Iolite 4 software (Elemental Scientific, Inc.).
Results: Our μCT findings show 6.9% (p=0.01) thinner incisor enamel in adult males exposed to ELS. No significant differences in molar or incisor enamel thickness are seen in adult females. On day 12, ELS males show 59% thinner molar enamel (p.0001), and females show 49.9% (p.0001) thinner molar enamel than controls. Moreover, differences in mandibular first molar mineral density are observed between male and female ELS groups compared to controls (n=49)(p.05). To our knowledge, this is the first study to show the presence of GABA- α1 receptors on mature ameloblasts of the continuously developing adult mouse incisor. We find differences in the timing of GABA- α1 expression between ELS and controls, with a slightly accelerated expression in ELS males. We also find a more robust expression of AR in the dental epithelium of ELS and control males compared to females. Our LA-ICP-MS analyses show differences in the hardness of enamel and dentin between ELS groups and controls. However, no differences in elemental composition were observed between groups.
Conclusion: The results of this study are consistent with the overall findings of sex-dependent responses to stress and an altered pace of development. To our knowledge, this is the first study to demonstrate the connection between ELS and GABA- α1 expression in dental tissues. Ultimately, our findings support the role of dental tissues as a possible biomarker of early life adversity.Oral Biolog
Supramolecular complex formation in bacterial anti-phage defense and viral immune evasion
No full textBacteria can encode many diverse nuclease-helicase defense systems that protect from viral infection and inhibit phage propagation. An emerging theme in anti-phage defense is the presence of nuclease-helicase operons. However, how nuclease-helicase systems defend against phage infection remains largely unknown. Gabija is one of the most prevalent nuclease-helicase defense systems, occurring in >15% of all sequenced bacterial and archaeal genomes. We discovered that Gabija proteins assemble into an ~500 kDa nuclease-helicase supramolecular complex that degrades phage DNA. Phages evolve diverse immune evasion mechanisms to inhibit host defense systems. We show that a phage-encoded protein, Gabija anti-defense 1 (Gad1), directly binds the Gabija complex by forming an octameric web inhibiting phage DNA recognition and cleavage. Phages can also encode another Gabija inhibitor, Gad2, which does not prevent Gabija DNA targeting in vitro, suggesting that Gad2 works upstream of DNA cleavage during infection. To understand nuclease-helicase system diversity, we biochemically screened 14 nuclease-helicase systems and found that they all form protein complexes of varying oligomeric state and have different phage nucleic acid cleavage specificity. Our results define mechanisms by which bacteria use nuclease-helicase anti-phage defense systems to inhibit viral infection and how phages fight back with unique viral immune evasion mechanisms.Virolog
Quantization, Sparsity, Reliability, and Their Interactions
No full textIn this thesis, we will explore and contribute to three seemingly disjoint areas of machine learning: quantization, sparsity, and reliability. While each of these areas are well-understood individually, there is very little existing literature on the interaction of these research areas. They are typically viewed as orthogonal to each other and solved independently. In this thesis, we would like to shed light on the fact that many practical systems employ elements from all three fields. Therefore, it is important to understand how they can influence and interact with each other.
This thesis makes the following three key contributions to the existing literature. First, it presents GoldenEye, a functional simulator for modeling fault injections into machine learning models. In particular, it targets models that use novel number formats to quantize or emulate to different data types. The flexible API design makes it easy to add new number formats as the area evolves. Furthermore, we propose a mathematical framework for using reliability analysis to inform quantization. Second, we present our work on EdgeBERT, an accelerator for accelerating transformer inference. EdgeBERT features both quantization and sparsity optimizations that together achieve strong speedups when profiled on true silicon. We also write compiler code that allows other transformer workloads to be compiled to EdgeBERT. Finally, we attempt to understand the problem of sequential applications of quantization and sparsity. We prove a theoretical result that shows that at the tensor-level sparsity before quantization is preferred over quantization before sparsity. However, we show that at the model level, the order is not too important, so long as the algorithms are "synergetic". Then, we propose a novel quantization-aware sparsity algorithm that consider the problem of sparsity when the weights are already quantized. Together, we believe that these contributions provide valuable insights to understanding the interactions between these distinct problems.Computer Scienc
Spectromer: a Visual Transformer-Based Model for Spectral Data
No full textWe present Spectromer, a novel framework leveraging Vision Transformers (ViTs), a class of deep learning models originally developed for image recognition, for the analysis of astronomical spectral data. By converting traditional one-dimensional
spectral data, where each spectrum is represented as a sequence of intensity values over wavelength, into two-dimensional image-like representations, Spectromer enables Vision Transformers to leverage their spatial self-attention mechanism for capturing both local and global spectral features.
We fine-tune a base model, pretrained on ImageNet, using images constructed from SDSS and LAMOST spectral data, which together encompass several million spectra from diverse astronomical objects. These images are generated by transforming one-dimensional spectral data into two-dimensional image representations suitable for vision transformer architectures. We then validate this model on key downstream tasks including stellar object classification and redshift estimation, demonstrating strong performance and scalability. Spectromer has provided either comparable or better results depending on downstream tasks with other models, showing similar R^2 to AstroCLIP’s spectrum encoder even when including data from different astronomical objects as well as showing higher classification accuracy versus solutions based on Support Vector Machine and Random Forests. Our results highlight Spectromer’s potential to advance spectral analysis by leveraging pretrained vision models to enable precise interpretation of large-scale astronomical datasets beyond their original design. To our knowledge, this is the first application of ViTs to spectroscopic data and among the first to demonstrate results on a large-scale, real observational dataset without relying on synthetic data.Extension Studie
Efficient Symbolic Execution and Reasoning for Low Level Code
No full textSystems should be correct, and automated reasoning promises to help construct correct systems. A common toolchain for automated reasoning about programs, used in program verification, program synthesis, and automated bug-finding, is symbolic execution and constraint solving. This dissertation describes the application and optimization of this toolchain in two projects. First, we discuss optimizing assembly program synthesis for OS porting with a deductive approach. Then, we introduce branch deferral, a way to optimize symbolic execution in bug-finding by reducing the number of paths explored when executing short-circuit control flow graphs.Engineering and Applied Sciences - Computer Scienc
Towards a Celestial Theory of Gravity, Gauge Theory, and Black Holes
No full textThe search for a consistent theory of quantum gravity in four-dimensional (4D) asymptotically flat spacetimes has led to the development of celestial holography, a framework in which 4D scattering amplitudes are recast as correlation functions in a two-dimensional (2D) conformal field theory living on the celestial sphere. This dissertation contributes new entries to this 4D--2D holographic dictionary, with applications to scattering theory, black holes, and aspects of supersymmetric gauge theories.
We begin by establishing a concrete correspondence between bulk scattering states and boundary CFT states. Boundary states can be constructed via the state-operator correspondence, where the celestial inner products are formulated from bulk inner products using a combination of shadow transforms and BPZ conjugation. This 2D reformulation organizes the scattering problem in a dramatically different way than in the 4D bulk, by mapping states between the hemispheres of the 2D boundary.
Next, we develop a direct map between black hole geometries and scattering amplitudes in signature, showing how linearized black hole spacetimes such as Kerr-Taub-NUT can be obtained from three-point graviton emission amplitudes. We also study the global structure of black holes via toric Penrose diagrams and show that the Kerr rotation parameter, , can be eliminated by a large diffeomorphism.
Following from these black hole results, we derive the celestial CFT dual of 4D linearized rotating self-dual black holes. This is accomplished by identifying the corresponding 2D ``black hole'' states as global conformal primaries on the celestial torus. These can be realized as coherent states of Goldstone modes, carrying an infinite tower of soft hair. We also draw connections to Wilson lines and celestial scattering in curved backgrounds.
Finally, we take steps towards the celestial dual for supersymmetric gauge theories. We find that the soft sector of these theories is realized as a chiral algebra on the boundary, and that the bulk electric-magnetic duality is realized as SL covariance of the celestial symmetry algebra. We also explore the boundary interpretation of the bulk moduli space singularities in terms of vertex operators constructed from soft and Goldstone modes.Physic