Miracle-dz/UniFAR-FTUs huggingface dataset:
Testing an Einstein's intuitive objection to quantum mechanics

We propose an experiment that allows one to test the Einstein’s intuitive objection to Bohr's quantum mechanics (QM), which was that if QM is correct, then there should be a nonlocality related to the collapse of a single-particle macroscopic wavefunction, which by no means is compatible with special relativity. The idea of the experiment is related to the so-called integer quantum Hall (IQH) systems known to have macroscopic quantum orbits often called extended states. The experiment appeared realizable in a modified IQH system and we have found that a single-particle nonlocality does exist precisely as it follows from QM. This fact makes one come back to the Bell-Popper idea to revive the Lorentz-Poincare “dynamic” version of relativity together with the classical concept of space and time. But now, if to add the single-particle nonlocality to the Bohm-Hiley model of undivided universe, one can solve the most formidable problem – to find a preferred reference frame without involving the vague notion “aether”. Moreover, now one can adopt a deeper-than-relativistic concept of what we call “reality”, which opens the door to a realistic interpretation of QM and, after all, to the awareness of the worldview of this extremely successful theory.
Rapid TAURUS for Relaxation-Based Color Magnetic Particle Imaging

Magnetic particle imaging (MPI) is a rapidly developing medical imaging modality that exploits the non-linear response of magnetic nanoparticles (MNPs). Color MPI widens the functionality of MPI, empowering it with the capability to distinguish different MNPs and/or MNP environments. The system function approach for color MPI relies on extensive calibrations that capture the differences in the harmonic responses of the MNPs. An alternative calibration-free x-space-based method called TAURUS estimates a map of the relaxation time constant, <inline-formula> <tex-math notation="LaTeX">$\tau $ </tex-math></inline-formula>, by recovering the underlying mirror symmetry in the MPI signal. However, TAURUS requires a back and forth scanning of a given region, restricting its usage to slow trajectories with constant or piecewise constant focus fields (FFs). In this work, we propose a novel technique to increase the performance of TAURUS and enable <inline-formula> <tex-math notation="LaTeX">$\tau $ </tex-math></inline-formula> map estimation for rapid and multi-dimensional trajectories. The proposed technique is based on correcting the distortions on mirror symmetry induced by time-varying FFs. We demonstrate via simulations and experiments in our in-house MPI scanner that the proposed method successfully estimates high-fidelity <inline-formula> <tex-math notation="LaTeX">$\tau $ </tex-math></inline-formula> maps for rapid trajectories that provide orders of magnitude reduction in scanning time (over 300 fold for simulations and over 8 fold for experiments) while preserving the calibration-free property of TAURUS.
Continuation Path with Linear Convergence Rate

Path-following algorithms are frequently used in composite optimization problems where a series of subproblems, with varying regularization hyperparameters, are solved sequentially. By reusing the previous solutions as initialization, better convergence speeds have been observed numerically. This makes it a rather useful heuristic to speed up the execution of optimization algorithms in machine learning. We present a primal dual analysis of the path-following algorithm and explore how to design its hyperparameters as well as determining how accurately each subproblem should be solved to guarantee a linear convergence rate on a target problem. Furthermore, considering optimization with a sparsity-inducing penalty, we analyze the change of the active sets with respect to the regularization parameter. The latter can then be adaptively calibrated to finely determine the number of features that will be selected along the solution path. This leads to simple heuristics for calibrating hyperparameters of active set approaches to reduce their complexity and improve their execution time.
Reconstructing Hamiltonians from Correlations and Entanglement

We investigate two methods to reconstruct Hamiltonians of quantum matter, using a quantum spin chain to test them. The first method uses correlation functions and the second method uses entanglement spectra. The two methods are not specific to spin chains, and may find wider applicability to quantum matter that is sufficiently well characterized by experiment.
Reversing the Lecture/Homework Paradigm Using eTEACH® Web‐based Streaming Video Software

A new online streaming video and multi‐media application called eTEACH, http:eTEACH.engr. wisc.edu was used to reform a large, lecture‐based computer science course for engineering majors. In‐class lectures were replaced with videotaped lectures and other materials that students viewed on the Internet on their own schedule, making it possible to use the live class periods for small, team problem‐solving sessions facilitated by the professors and a teaching assistant. By using the eTEACH application to transform course lectures into “homework” and free up the face‐to‐face class time for working on problems that were similar to homework assignments, the professors effectively reversed the lecture and homework paradigm of a typical large lecture course. A thorough course evaluation over two semesters showed that students who took the online lecture version of the course gave significantly higher ratings to all aspects of the course, including lecture usefulness, professor responsiveness, the course overall, and the instructor. Although a few students missed having the opportunity to ask questions during lectures, about two‐thirds of the 531 students surveyed felt it was easier to take notes and understand the lectures presented via eTEACH than it would have been while attending the same lecture live, and 78% of students appreciated the ability to view and review course lectures on their own schedule.
Multiple lattice instabilities and complex ground state in Cs$_2$AgBiBr$_6$

Metal halides perovskites (MHPs) are attracting considerable interest for optoelectronic applications, with Cs$_2$AgBiBr$_6$ one of the main contenders among lead-free systems. Cs$_2$AgBiBr$_6$ crystallizes in a nominally double-perovskite structure, but exhibits a soft lattice with large atomic fluctuations characteristic of MHPs. While crucial to understand electron-phonon and phonon-phonon couplings, the spatio-temporal correlations of these fluctuations remain largely unknown. Here, we reveal these correlations using comprehensive neutron and x-ray scattering measurements on Cs$_2$AgBiBr$_6$ single-crystals, complemented with first-principles simulations augmented with machine-learned neural-network potentials. We report the discovery of an unexpected complex modulated ground state structure containing several hundred atoms, arising from a soft-phonon instability of the low-temperature tetragonal phase. Further, our experiments and simulations both reveal extensive correlated 2D fluctuations of Br octahedra at finite temperature, arising from soft anharmonic optic phonons, reflecting very shallow potential wells. These results provide new insights into the atomic structure and fluctuations in MHPs, critical to understand and control their thermal and optoelectronic properties.
Reionization in the Light of Dark Stars

We investigate the effect of dark stars (DSs) on the reionization history of the universe, and the interplay between them and feedback due to Lyman–Werner (LW) radiation in reducing the cosmic microwave background (CMB) optical depth to a value within the τ = 0.054 ± 0.007 range measured by Planck. We use a semianalytic approach to evaluate reionization histories and CMB optical depths, which includes Population II stars in atomic cooling halos and Population III stars in minihalos with LW feedback, preceded by a DS phase. We show that while LW feedback by itself can reduce the integrated optical depth to the last scattering surface to ∼0.05 only if the Population III star formation efficiency is less than ∼0.2%, the inclusion of a population of DSs can naturally lead to the measured CMB optical depth for much larger Population III star formation efficiencies ≳1%.
Methanol Mapping in Cold Cores: Testing Model Predictions

Chemical models predict that in cold cores gas-phase methanol is expected to be abundant at the outer edge of the CO depletion zone, where CO is actively adsorbed. CO adsorption correlates with volume density in cold cores, and, in nearby molecular clouds, catastrophic CO freeze-out happens at volume densities above 104 cm−3. The methanol production rate is maximized there and its freeze-out rate does not overcome its production rate, while the molecules are shielded from UV destruction by gas and dust. Thus, in cold cores, methanol abundance should generally correlate with visual extinction, which depends on both volume and column density. In this work, we test the most basic model prediction that maximum methanol abundance is associated with a local A V ∼ 4 mag in dense cores and constrain the model parameters with the observational data. With the IRAM 30 m antenna, we mapped the CH3OH (2–1) and (3–2) transitions toward seven dense cores in the L1495 filament in Taurus to measure the methanol abundance. We use the Herschel/SPIRE maps to estimate visual extinction, and the C18O(2–1) maps from Tafalla & Hacar to estimate CO depletion. We explored the observed and modeled correlations between the methanol abundances, CO depletion, and visual extinction, varying the key model parameters. The modeling results show that hydrogen surface diffusion via tunneling is crucial to reproduce the observed methanol abundances, and the necessary reactive desorption efficiency matches the one deduced from laboratory experiments.
Explainability of the Implications of Supervised and Unsupervised Face Image Quality Estimations Through Activation Map Variation Analyses in Face Recognition Models

It is challenging to derive explainability for unsupervised or statistical-based face image quality assessment (FIQA) methods. In this work, we propose a novel set of explainability tools to derive reasoning for different FIQA decisions and their face recognition (FR) performance implications. We avoid limiting the deployment of our tools to certain FIQA methods by basing our analyses on the behavior of FR models when processing samples with different FIQA decisions. This leads to explainability tools that can be applied for any FIQA method with any CNN-based FR solution using activation mapping to exhibit the network’s activation derived from the face embedding. To avoid the low discrimination between the general spatial activation mapping of low and high-quality images in FR models, we build our explainability tools in a higher derivative space by analyzing the variation of the FR activation maps of image sets with different quality decisions. We demonstrate our tools and analyze the findings on four FIQA methods, by presenting inter and intra-FIQA method analyses. Our proposed tools and the analyses based on them point out, among other conclusions, that high-quality images typically cause consistent low activation on the areas outside of the central face region, while low-quality images, despite general low activation, have high variations of activation in such areas. Our explainability tools also extend to analyzing single images where we show that low-quality images tend to have an FR model spatial activation that strongly differs from what is expected from a high-quality image where this difference also tends to appear more in areas outside of the central face region and does correspond to issues like extreme poses and facial occlusions. The implementation of the proposed tools is accessible here 1.1https://github.com/fbiying87/Explainable_FIQA_WITH_AMVA
Single-event current transients induced by high energy ion microbeams

Focused high-energy ion microbeams were applied to the study of the basic mechanisms of single-event upset. Waveforms of the current transients induced by He-, C-, O- and Fe-ion strikes on silicon diodes were measured by applying extremely low beam currents of an order of 10 fA and a wide-bandwidth digitizing sampling technique. Total collected charges are evaluated from the transient currents as a function of LET (linear energy transfer), bias voltage, and doping level, and are compared with theoretical values calculated using conventional single-event models. It is found that irradiation effects on the total collected charges can be explained by the introduction of displacement atoms calculated using Coulomb potential and the Kinchin-Pease model. >
Designing Web Usability: The Practice of Simplicity

From the Publisher: Can you afford to be less knowledgable than your competitors? Over 100,000 Internet professionals around the world have already bought this book. Users experience the usability of a site before they have committed to using it and before they have spent any money on potential purchases. The web is the ultimate environment for empowerment, and he or she who clicks the mouse decides everything. Jakob Nielson, shares with you the full weight of his wisdom and experience. From content and page design to designing for ease of navigation and users with disabilities, Nielsen delivers complete direction on how to connect with any web user, in any situation. Nielsen has arrived at a series of principles that work in support of his findings: 1. that web users want to find what they're after quickly, and 2. if they don't know what they're after, they nevertheless want to browse quickly and access information they come across in a logical manner.
Capacity Discipline and the Consolidation of Airport Connectivity in the United States

Airlines reduced available domestic capacity at airports across the United States from 2007 to 2012 in response to a global economic downturn and high and volatile fuel prices. More recently, despite an economic recovery and more stable fuel prices, airlines have continued to keep capacity low relative to historical levels in a strategy that has been referred to as “capacity discipline. ” The effects of these shifts in capacity on airport connectivity to the global air transportation network remain unclear. This paper introduces an intuitive index to compute airport connectivity as a function of both the quantity and quality of scheduled nonstop and connecting service. Connectivity scores were computed for 462 U.S. airports; medium-hub and small-hub airports were found to have lost more connectivity on average than large-hub airports from 2007 to 2012. In multiairport regions, losses in connectivity at secondary and tertiary airports outpaced losses at primary airports. With lower levels of connectivity, smaller airports in these regions will need to employ creative strategies to prevent passengers from leaking to primary hubs. Whether these airports can recover from connectivity consolidation will also depend on how long the capacity discipline equilibrium remains in effect among U.S. airlines.
Calibration Improves Bayesian Optimization

Bayesian optimization is a procedure that allows obtaining the global optimum of black-box functions and that is useful in applications such as hyper-parameter optimization. Uncertainty estimates over the shape of the objective function are instrumental in guiding the optimization process. However, these estimates can be inaccurate if the objective function violates assumptions made within the underlying model (e.g., Gaussianity). We propose a simple algorithm to calibrate the uncertainty of posterior distributions over the objective function as part of the Bayesian optimization process. We show that by improving the uncertainty estimates of the posterior distribution with calibration, Bayesian optimization makes better decisions and arrives at the global optimum in fewer steps. We show that this technique improves the performance of Bayesian optimization on standard benchmark functions and hyperparameter optimization tasks.
Covariate Balancing Sensitivity Analysis for Extrapolating Randomized Trials across Locations

The ability to generalize experimental results from randomized control trials (RCTs) across locations is crucial for informing policy decisions in targeted regions. Such generalization is often hindered by the lack of identifiability due to unmeasured effect modifiers that compromise direct transport of treatment effect estimates from one location to another. We build upon sensitivity analysis in observational studies and propose an optimization procedure that allows us to get bounds on the treatment effects in targeted regions. Furthermore, we construct more informative bounds by balancing on the moments of covariates. In simulation experiments, we show that the covariate balancing approach is promising in getting sharper identification intervals.
Prompt-based Zero-shot Relation Classification with Semantic Knowledge Augmentation

In relation classification, recognizing unseen 001 (new) relations for which there are no training 002 instances is a challenging task. We propose 003 a prompt-based model with semantic knowl- 004 edge augmentation (ZS-SKA) to recognize un- 005 seen relations under the zero-shot setting. We 006 present a new word-level sentence translation 007 rule and generate augmented instances with 008 unseen relations from instances with seen rela- 009 tions using that new rule. We design prompts 010 based on an external knowledge graph to inte- 011 grate semantic knowledge information learned 012 from seen relations. Instead of using the actual 013 label sets in the prompt template, we construct 014 weighted virtual label words. We learn the rep- 015 resentations of both seen and unseen relations 016 with augmented instances and prompts. We 017 then calculate the distance between the gen- 018 erated representations using prototypical net- 019 works to predict unseen relations. Extensive 020 experiments conducted on three public datasets 021 show that ZS-SKA outperforms state-of-the-art 022 methods under the zero-shot scenarios. Our 023 experimental results also demonstrate the effec- 024 tiveness and robustness of ZS-SKA. 025
Harmonic and non-Harmonic Based Noisy Reverberant Speech Enhancement in Time Domain

This paper introduces the single step time domain method named HnH-NRSE, whihc is designed for simultaneous speech intelligibility and quality improvement under noisyreverberant conditions. In this solution, harmonic and nonharmonic elements of speech are separated by applying zerocrossing and energy criteria. An objective evaluation of the its non-stationarity degree is further used for an adaptive gain to treat masking components. No prior knowledge of speech statistics or room information is required for this technique. Additionally, two combined solutions, IRMO and IRMN, are proposed as composite methods for improvement on noisyreverberant speech signals. The proposed and baseline methods are evaluated considering two intelligibility and three quality measures, applied for the objective prediction. The results show that the proposed scheme leads to a higher intelligibility and quality improvement when compared to competing methods in most scenarios. Additionally, a perceptual intelligibility listening test is performed, which corroborates with these results. Furthermore, the proposed HnH-NRSE solution attains SRMR quality measure with similar results when compared to the composed IRMO and IRMN techniques.
Modelling Lips-State Detection Using CNN for Non-Verbal Communications

Vision-based deep learning models can be promising for speech-and-hearing-impaired and secret communications. While such non-verbal communications are primarily investigated with hand-gestures and facial expressions, no research endeavour is tracked so far for the lips state (i.e., open/close)-based interpretation/translation system. In support of this development, this paper reports two new Convolutional Neural Network (CNN) models for lips state detection. Building upon two prominent lips landmark detectors, DLIB and MediaPipe, we simplify lips-state model with a set of six key landmarks, and use their distances for the lips state classification. Thereby, both the models are developed to count the opening and closing of lips and thus, they can classify a symbol with the total count. Varying frame-rates, lips-movements and face-angles are investigated to determine the effectiveness of the models. Our early experimental results demonstrate that the model with DLIB is relatively slower in terms of an average of 6 frames per second (FPS) and higher average detection accuracy of 95.25%. In contrast, the model with MediaPipe offers faster landmark detection capability with an average FPS of 20 and detection accuracy of 94.4%. Both models thus could effectively interpret the lips state for non-verbal semantics into a natural language.
Protein biomarkers in serum as a conservation tool to assess reproduction: a case study on brown bears (Ursus arctos)

Abstract Monitoring the reproductive characteristics of a species can complement existing conservation strategies by understanding the mechanisms underlying demography. However, methodology to determine important aspects of female reproductive biology is often absent in monitoring programs for large mammals. Protein biomarkers may be a useful tool to detect physiological changes that are indicative of reproductive state. This study aimed to identify protein biomarkers of reproductive status in serum collected from free-ranging female brown bears (Ursus arctos) in Alberta, Canada, from 2001 to 2018. We hypothesized that the expression of proteins related to reproduction in addition to energetics and stress can be used to answer specific management-focused questions: (i) identify when a female is pregnant, (ii) detect if a female is lactating, (iii) determine age of sexual maturity (i.e. primiparity) and (iv) assess female fertility (i.e. reproduction rate). Furthermore, we investigated if silver spoon effects (favourable early life conditions provide fitness benefits through adulthood) could be determined using protein expression. A target panel of 19 proteins with established relationships to physiological function was measured by peptide-based analysis using liquid chromatography and multiple reaction monitoring mass spectrometry and their differential expression was evaluated using a Wilcoxon signed-rank test. We found biomarkers of pregnancy (apolipoprotein B-100 and afamin), lactation (apolipoprotein B-100 and alpha-2-macroglobulin) and sexual maturity (corticosteroid-binding globulin), but there were no statistically significant relationships with protein expression and fertility. The expression of proteins related to reproduction (afamin) and energetics (vitamin-D binding protein) was associated with the nutritional quality of the individual’s present habitat rather than their early life habitat. This study highlights potential biomarkers of reproductive status and provides additional methods for monitoring physiological function in wildlife to inform conservation.