Miracle-dz/UniFAR-FTUs huggingface dataset:
Three-Dimensional Feature Models for Synthetic Aperture Radar and Experiments in Feature Extraction

This dissertation presents a new set of three-dimensional scattering feature models for synthetic aperture radar (SAR). We develop a set of parametric models of canonical shapes that capture aspect-dependent, high-frequency scattering for bistatic (and monostatic) 3D SAR phase history responses. The models are parameterized by the shape location, orientation, and size as well as the radar transmitter and receiver antenna aspects and frequency. We develop the models by combining physical optics (PO) and uniform theory of diffraction (UTD) planar scattering solutions to approximate 3D scattering responses of canonical shapes. We validate the models using scattering prediction software and show that the proposed models capture well the mainlobe responses of each shape. Thus, the proposed models may be used to accurately predict first-order scattering of scenes comprised of such shapes. The second part of this dissertation focuses on the inverse problem of discerning the types of canonical shapes in a scene and estimating their corresponding model parameters from observed SAR phase history data. We present discrimination methods for classifying observed scattering into the geometric shape types. We compute the Cramér-Rao bounds for the models and characterize model parameter estimation accuracy for two estimation schemes. Finally, we present a feature extraction algorithm that classifies and estimates the canonical features from polarimetric phase history data. We use non-quadratic regularization to form sparsity-constrained 3D ii SAR images that are used to initialize the scatterer location, orientation, and size estimates. We test the feature extraction algorithm on simulated phase histories for densely-sampled and sparsely-sampled, monostatic and bistatic 3D SAR apertures. We show that even for sparsely-sampled apertures, the feature extraction algorithm is able to estimate geometric scattering features in the scene. Feature extraction for the proposed canonical shape models may be extended in future work for use in automatic target recognition.
Experiences of participating in a structured osteoporosis school in persons with established spinal osteoporosis – an interview study

Introduction: Patient education in combination with physical activity has been proposed as a way of increasing health-related quality of life and functional capacity in patients with osteoporosis. A randomised pilot study called the School of Osteoporosis in Link € oping (SOL) was conducted in 2018 for persons aged � 60years with established spinal osteoporosis. The SOL was scheduled for ten weeks with once-weekly theory education with or without additional supervised physical group training. The purpose of the present study was to explore the experiences of having participated in an osteoporosis school in persons with established spinal osteoporosis. Materials and methods: Ten participants who had completed the SOL with patient education and supervised physical group training were invited to individual interviews, while six persons were accepted to participate. Qualitative content analysis was conducted with an inductive approach. Findings: Three main categories were identified from the interviews: The structure of the osteoporosis school; Gained knowledge related to the education in the osteoporosis school; and Experiences of health status one-year post-intervention. Seven associated subcategories were identified. Increased knowledge and perceptions of improved health acquired by the interventions were emphasised. However, continued supervised group training was requested and there were also concerns about worsened health at the one-year post-intervention follow-up. Conclusion: The tailored content and the group aspects of the structured osteoporosis school were experienced as the most important factors for successful results.
Stokes operator and stability of stationary Navier-Stokes flows in infinite cylindrical domains

infinite cylindrical domains have been attracting great attention due to its theoretical and practical significance. However, in most cases, stationary Navier-Stokes problems were dealt with whereas instationary Navier-Stokes problems have been less studied. The Lq-approach to instationary Navier-Stokes problems is very important and convenient to analyze existence, uniqueness as well as strong energy inequality and partial regularity for solutions; to this end, the study of the Stokes operator is fundamental. The aim of this dissertation is to get resolvent estimates, maximal regularity and boundedness of H∞-calculus of Stokes operators in infinite cylindrical domains and to apply them to the stability of stationary Navier-Stokes flows in infinite cylindrical domains. We start with a Stokes resolvent system in an infinite straight cylinder. The Stokes resolvent system on an infinite straight cylinder is reduced by the (one-dimensional) partial Fourier transform along the axis of the cylinder to a parametrized Stokes system with the Fourier variable as a parameter. Using the Fourier multiplier theory in weighted spaces we get estimates for the parametrized Stokes system with bound constants independent of parameters. Based on these estimates resolvent estimate and maximal regularity of the Stokes operator in weighted Lebesgue spaces on an infinite straight cylinder are shown using the techniques of operator-valued Fourier multiplier theory and Schauder decomposition in Banach spaces with UMD property. Next we consider the Stokes operator in general infinite cylinders with several exits to infinity. A resolvent estimate of the Stokes operator in Lq-space is obtained using cut-off techniques based on the result of generalized Stokes resolvent system in an infinite straight cylinder. In particular, the Stokes operator is shown to generate a bounded and exponentially decaying analytic semigroup in any Lq-space on a general infinite cylinder. Moreover, it is proved that the Stokes operator admits a bounded H∞-calculus in any Lq-space on an infinite cylinder with several exits to infinity. As an application of the obtained properties of the Stokes operator we study stability of stationary Navier-Stokes flows in infinite cylindrical domains. First, existence and uniqueness for stationary Navier-Stokes systems in infinite cylinders are shown. Then the exponential stability of the stationary Navier-Stokes flow is proved based on Lr-Lq estimates of the perturbed Stokes semigroup.
Study on Chemical Behavior of Energetic Deuterium Implanted into Li2TiO3

Abstract Deuterium ion implantation and subsequent X-ray Photoelectron Spectroscopy (XPS) and Thermal Desorption Spectroscopy (TDS) experiments were performed with varying implantation temperatures to reveal chemical behavior of tritium produced in Li2TiO3. These experimental results showed that there were four deuterium trapping states; two of which were interacted with and without oxygen near the surface, and the other two were interacted with E’-center and with oxygen with the formation of O-D bond in the bulk. These trapping states of deuterium in the bulk were almost the same as those of tritium generated in thermal neutron-irradiated Li2TiO3. The total amount of deuterium retention in the bulk was almost constant until O-D bonds formed in the bulk were decomposed, indicating that tritium trapping could proceed under hot atom chemical reactions. It was concluded that E’-center could trap the implanted deuterium more frequently than oxygen with the formation of O-D bonds in the bulk. Annihilations of them due to oxygen recovery could increase the retention of D with the formation of O-D bonds, resulting in the almost constant deuterium retention ratio up to its decomposition temperature of 573 K.
Latinx’s Attention to Social Context: A Comparison with European Americans and East Asians Living in the U.S.

Prior research shows that collectivistic East Asians are more sensitive to contextual information than individualistic Americans. However, limited studies have explored other collectivistic societies, such as the Latinx. Extending the current literature, we investigated attention to social context among Latinx living in the United States. Two tasks were used to test how Latinx (N=260) incorporate social context information when making attributions as compared to European Americans (N=220) and East Asians (N=144) living in the United States. In Task 1, participants made attributions about their friend’s career choice. In Task 2, participants made attributions about a character experiencing constraints in a semi-real-life situation. The findings demonstrated that when making attributions, East Asians were more attentive to social context than European Americans. Furthermore, Latinx were attentive to social context like the East Asians, but findings were not consistent across tasks. Results are discussed as a function of cultural frameworks, specifically from the perspectives of European American and East Asian cultures, and from the Latinx cultures. The role of collectivism on holistic thinking and practical implications of culture-driven attention style are discussed. Directions for future research are also suggested.
Ethnic Variability in Glucose and Insulin Response to Rice Among Healthy Overweight Adults: A Randomized Cross-Over Study

Background The influence of ethnicity on postprandial glucose and insulin responses has been reported earlier and rice is a major contributor to the overall glycaemic load of Asian and Arab diets. This study aims to compare postprandial glycaemic and insulinaemic responses to rice among healthy overweight Asian, Arab and European participants. Methods In a randomized crossover design, 47 healthy overweight participants (23 Asian, 16 Arab, and 8 European) consumed 75 grams of glucose beverage or ate 270 grams of cooked basmati rice (75 g of available carbohydrate) on two separate occasions, separated by a one 1-week washout period. Blood glucose and insulin levels were determined at fasting 0 (fasting), 30, 60, and 120 minutes and used to determine the incremental area under the curve (iAUC). Results The three groups were matched on body mass index and gender. Although no differences were noted statistically in most clinical features, a wide range of variation was noted in age, systolic, diastolic blood pressure. The fasting blood glucose and insulin levels were highest among Asians, followed by Arabs and Europeans (p < 0.01). According to the HOMA-IR test and the Matsuda index, Asians have a higher insulin resistance than Arabs or Europeans when consuming a glucose beverage (p < 0.001) and rice (p < 0.01). Postprandial glucose and insulin responses to glucose beverage did not differ between ethnic groups (p = 0.28; p = 0.10). Based on an unadjusted regression model, European participants had significantly lower iAUC-glucose (p = 0.02) and iAUC-insulin (p = 0.01) after rice consumption than Asian participants. In the adjusted model, the difference between the two groups remained for iAUC-insulin (p = 0.04) but not for iAUC-glucose (p = 0.07). Conclusion Our study found that ethnic differences exist among healthy overweight adults in terms of insulin resistance, glycaemic response and insulinaemic response to rice. As a result of their high insulin resistance, Asian participants had a higher postprandial insulin spike than Europeans after eating rice. These findings could have substantial implications for nutrition recommendations based on ethnicity, particularly for Asians.
Quantum theory is exclusive: a distributed computing setup

The framework of distributed computing, consisting of several spatially separated input-output servers, has immense importance in distant data manipulation. One of the most challenging parts of this setting is to optimize the use of information transmission lines among distant servers. In this work, we have modeled such a physically motivated distributed computing setup for which quantum communication outperforms its classical counterpart, in terms of a limited usage of noiseless transmission lines. Moreover, a broader class of communication entities, that allow state-effect description more exotic than quantum and are described within the framework of generalized probabilistic theory, also fail to meet the strength of quantum theory. The computational strength of quantum communication has further been justified in terms of a stronger version of this task, namely the delayed-choice distributed computation. The proposed task thus provides a new approach to operationally single out quantum theory in the theory-space and hence promises a novel perspective towards the axiomatic derivation of Hilbert space quantum mechanics.
Reflection vectors and quantum cohomology of blowups

Let $X$ be a smooth projective variety with a semi-simple quantum cohomology. It is known that the blow up $Bl(X)$ of $X$ at one point also has semi-simple quantum cohomology. In particular, the monodromy group of the quantum cohomology of $Bl(X)$ is a reflection group. We found explicit formulas for certain generators of the monodromy group of the quantum cohomology of $Bl(X)$ depending only on the geometry of the exceptional divisor.
Soliton resolution for nonlinear Schr\"odinger type equations in the radial case

We consider the Schr\"odinger equation with a general interaction term, which is localized in space, for radially symmetric initial data in $n$ dimensions, $n\geq5$. The interaction term may be space-time dependent and nonlinear. Assuming that the solution is bounded in $H^1(\mathbb{R}^n)$ uniformly in time, we prove soliton resolution conjecture (Asymptotic completeness) by demonstrating that the solution resolves into a smooth and localized part and a free radiation in $\mathcal{L}^2_x(\mathbb{R}^n)$ norm. Examples of such equations include inter-critical and super-critical nonlinear Schr\"odinger equations, saturated nonlinearities, time-dependent potentials, and combinations of these terms.
Bridging Nations: Quantifying the Role of Multilinguals in Communication on Social Media

Social media enables the rapid spread of many kinds of information, from pop culture memes to social movements. However, little is known about how information crosses linguistic boundaries. We apply causal inference techniques on the European Twitter network to quantify the structural role and communication influence of multilingual users in cross-lingual information exchange. Overall, multilinguals play an essential role; posting in multiple languages increases betweenness centrality by 13%, and having a multilingual network neighbor increases monolinguals’ odds of sharing domains and hashtags from another language 16-fold and 4-fold, respectively. We further show that multilinguals have a greater impact on diffusing information is less accessible to their monolingual compatriots, such as information from far-away countries and content about regional politics, nascent social movements, and job opportunities. By highlighting information exchange across borders, this work sheds light on a crucial component of how information and ideas spread around the world.
Quantitative Convergence for Displacement Monotone Mean Field Games with Controlled Volatility

We study the convergence problem for mean field games with common noise and controlled volatility. We adopt the strategy recently put forth by Laurière and the second author, using the maximum principle to recast the convergence problem as a question of “forward-backward propagation of chaos” (i.e., (conditional) propagation of chaos for systems of particles evolving forward and backward in time). Our main results show that displacement monotonicity can be used to obtain this propagation of chaos, which leads to quantitative convergence results for open-loop Nash equilibria for a class of mean field games. Our results seem to be the first (quantitative or qualitative) that apply to games in which the common noise is controlled. The proofs are relatively simple and rely on a well-known technique for proving wellposedness of forward-backward stochastic differential equations, which is combined with displacement monotonicity in a novel way. To demonstrate the flexibility of the approach, we also use the same arguments to obtain convergence results for a class of infinite horizon discounted mean field games. Funding: J. Jackson is supported by the National Science Foundation [Grant DGE1610403]. L. Tangpi is partially supported by the National Science Foundation [Grants DMS-2005832 and DMS-2143861].
A Comparison of Outflow Properties in AGN Dwarfs versus Star-forming Dwarfs

Feedback likely plays a crucial role in resolving discrepancies between observations and theoretical predictions of dwarf galaxy properties. Stellar feedback was once believed to be sufficient to explain these discrepancies, but it has thus far failed to fully reconcile theory and observations. The recent discovery of energetic galaxy-wide outflows in dwarf galaxies hosting active galactic nuclei (AGNs) suggests that AGN feedback may have a larger role in the evolution of dwarf galaxies than previously suspected. In order to assess the relative importance of stellar versus AGN feedback in these galaxies, we perform a detailed Keck/KCWI optical integral field spectroscopic study of a sample of low-redshift star-forming (SF) dwarf galaxies that show outflows in ionized gas in their Sloan Digital Sky Survey spectra. We characterize the outflows and compare them to observations of AGN-driven outflows in dwarfs. We find that SF dwarfs have outflow components that have comparable widths (W 80) to those of outflows in AGN dwarfs, but are much less blueshifted, indicating that SF dwarfs have significantly slower outflows than their AGN counterparts. Outflows in SF dwarfs are spatially resolved and significantly more extended than those in AGN dwarfs. The mass-loss, momentum, and energy rates of star-formation-driven outflows are much lower than those of AGN-driven outflows. Our results indicate that AGN feedback in the form of gas outflows may play an important role in dwarf galaxies and should be considered along with SF feedback in models of dwarf galaxy evolution.
Deep Image Matting: A Comprehensive Survey

Image matting refers to extracting precise alpha matte from natural images, and it plays a critical role in various downstream applications, such as image editing. Despite being an ill-posed problem, traditional methods have been trying to solve it for decades. The emergence of deep learning has revolutionized the field of image matting and given birth to multiple new techniques, including automatic, interactive, and referring image matting. This paper presents a comprehensive review of recent advancements in image matting in the era of deep learning. We focus on two fundamental sub-tasks: auxiliary input-based image matting, which involves user-defined input to predict the alpha matte, and automatic image matting, which generates results without any manual intervention. We systematically review the existing methods for these two tasks according to their task settings and network structures and provide a summary of their advantages and disadvantages. Furthermore, we introduce the commonly used image matting datasets and evaluate the performance of representative matting methods both quantitatively and qualitatively. Finally, we discuss relevant applications of image matting and highlight existing challenges and potential opportunities for future research. We also maintain a public repository to track the rapid development of deep image matting at https://github.com/JizhiziLi/matting-survey.
ForamViT-GAN: Exploring New Paradigms in Deep Learning for Micropaleontological Image Analysis

In geosciences, micropaleontology studies the evolution of microfossils (e.g., foraminifera) throughout geological records and utilizes such information to reconstruct past environmental and climatic conditions. This field depends primarily on the visual recognition of various features in microfossils, which makes it ideal for applying computer vision technology, specifically deep convolutional neural networks (CNNs), to automate and optimize different microfossil identification and classification. In addition, the unlabeled, low-resolution micropaleontological dataset is often available in a large volume compared to another geosciences dataset. While the application of deep learning in micropaleontology is rapidly growing, these efforts have been severely hampered by (i) the limited availability of high-quality and high-resolution labeled fossil images and (ii) significant effort in manually labeling various fossils by subject matter experts. Furthermore, previous works primarily exploited CNN with transfer learning to obtain high-accuracy prediction, which may reduce the explainability and reproducibility of the model. To overcome this issue, we propose a novel deep learning workflow that couples hierarchical vision transformers with style-based generative adversarial network algorithms to efficiently acquire and synthetically generate realistic high-resolution labeled datasets of micropaleontology in a large volume. Our study demonstrates that the proposed workflow could generate high-resolution images with a high signal-to-noise ratio, achieving 39.1 dB, and realistic synthetic images with a Fréchet inception distance similarity score of 14.88. In addition, our proposed workflow could provide a considerable volume of self-labeled datasets that can be used for model benchmarking and various downstream visual tasks, including fossil classification and segmentation. We further performed, for the first time, a few-shot semantic segmentation of different foraminifera chambers on both the generated and synthetic images with high accuracy. This novel meta-learning approach is only possible when a high-resolution and high-volume labeled dataset is available. Therefore, our proposed deep learning-based workflow is promising and shows a potential to advance and optimize micropaleontological research and other visual-dependent geological analysis.
Enhanced and reduced solute transport and flow strength in salt finger convection in porous media

We report a pore-scale numerical study of salt finger convection in porous media, with a focus on the influence of the porosity in the non-Darcy regime, which has received little attention in previous research. The numerical model is based on the lattice Boltzmann method with a multiple-relaxation-time scheme and employs an immersed boundary method to describe the fluid–solid interaction. The simulations are conducted in a two-dimensional, horizontally periodic domain with an aspect ratio of 4, and the porosity [Formula: see text] is varied from 0.7 to 1, while the solute Rayleigh number [Formula: see text] ranges from [Formula: see text] to [Formula: see text]. Our results show that, for all explored [Formula: see text], solute transport first enhances unexpectedly with decreasing [Formula: see text] and then decreases when [Formula: see text] is smaller than a [Formula: see text]-dependent value. On the other hand, while the flow strength decreases significantly as [Formula: see text] decreases at low [Formula: see text], it varies weakly with decreasing [Formula: see text] at high [Formula: see text] and even increases counterintuitively for some porosities at moderate [Formula: see text]. Detailed analysis of the salinity and velocity fields reveals that the fingered structures are blocked by the porous structure and can even be destroyed when their widths are larger than the pore scale, but become more ordered and coherent with the presence of porous media. This combination of opposing effects explains the complex porosity dependencies of solute transport and flow strength. The influence of porous structure arrangement is also examined, with stronger effects observed for smaller [Formula: see text] and higher [Formula: see text]. These findings have important implications for passive control of mass/solute transport in engineering applications.