Miracle-dz/UniFAR-FTUs huggingface dataset:
Testing the Acceptability and Usability of an AI-Enabled COVID-19 Diagnostic Tool Among Diverse Adult Populations in the United States

Background and Objectives: Although at-home coronavirus disease-2019 (COVID-19) testing offers several benefits in a relatively cost-effective and less risky manner, evidence suggests that at-home COVID-19 test kits have a high rate of false negatives. One way to improve the accuracy and acceptance of COVID-19 screening is to combine existing at-home physical test kits with an easily accessible, electronic, self-diagnostic tool. The objective of the current study was to test the acceptability and usability of an artificial intelligence (AI)-enabled COVID-19 testing tool that combines a web-based symptom diagnostic screening survey and a physical at-home test kit to test differences across adults from varying races, ages, genders, educational, and income levels in the United States. Methods: A total of 822 people from Richmond, Virginia, were included in the study. Data were collected from employees and patients of Virginia Commonwealth University Health Center as well as the surrounding community in June through October 2021. Data were weighted to reflect the demographic distribution of patients in United States. Descriptive statistics and repeated independent t tests were run to evaluate the differences in the acceptability and usability of an AI-enabled COVID-19 testing tool. Results: Across all participants, there was a reasonable degree of acceptability and usability of the AI-enabled COVID-19 testing tool that included a physical test kit and symptom screening website. The AI-enabled COVID-19 testing tool demonstrated overall good acceptability and usability across race, age, gender, and educational background. Notably, participants preferred both components of the AI-enabled COVID-19 testing tool to the in-clinic testing. Conclusion: Overall, these findings suggest that our AI-enabled COVID-19 testing approach has great potential to improve the quality of remote COVID testing at low cost and high accessibility for diverse demographic populations in the United States.
Application of Spectral Analysis to Detection of Space Charge Distribution in Solid Dielectrics

— The paper deals with the signal processing of ultrasonic pulses to obtain information on space charge distribution is solid dielectrics. The linear theory based on the Fourier transform is applied to the study of ultrasonic wave propagation along the measuring path. Application of spectral method simplifies a signal analysis and enables description of the pulse and step responses accurately. The compiled computer procedures, which include FFT computer programs permit direct processing of measured signals that are stored in memory of oscilloscope.
UBVRI PHOTOMETRY OF THE OPEN CLUSTER COLLINDER 359, ALLEGED TO CONTAIN W URSAE MAJORIS SYSTEMS.

The present note contributes to the question of the existence of Cr 359. On the basis of the UBV(RI)C photometry for all 13 stars, the author shows that nine stars of the original cluster may form a common main sequence, a fact which may be an indication of the physical association of these stars.
CME323 Report: Distributed Multi-Armed Bandits

Consider the multi-armed bandit (MAB) problem. In this sequential optimization problem, a player gets to pull one of K arms at every time instant. Arm i when pulled yields a reward Yi,k iid ∼ Pi. The distribution and means of the rewards for each arm are unknown. The goal of the player is the maximize rewards or minimize regret (difference between an oracle who knows the distribution of rewards and the player). MAB problems are used in online ad placement, ranking of search results, accelerating model selection among other applications. There is a balance between exploring arms which have not been seen before and exploiting the arm that is seen till now to offer the best rewards. The analysis of the multiarmed bandit problem was given by Gittens [1]. Upper Confidence Bound and a variant of online gradient approach to solving the single player case was proposed by Auer et al [2]. The analysis of Posterior Sampling was done in [3]. In this project, we consider the distributed version of the problem where there are n players distributed on a network. Each node plays the game in parallel and can communicate with their neighbour. We investigate how much cooperation can help players converge to the optimal arm. A version of this problem was studied in Liu [4] where players play with common arms and there are collisions if multiple players pick the same arm. There is no communication between players. In [5], the distributed bandit problem in considered on a P2P network where any node can communicate with any other node. A distributed -greedy approach was mooted and an analysis for a simplified case was presented. Finally, in [6], the impact of infrequent all-to-all communication on the convergence of distributed multiarmed bandits is analysed. In this work, we extend the online gradient approach to the distributed network case.
Transcriptomic Analysis of Ulva prolifera in Response to Salt Stress

Since 2007, Ulva prolifera, a green macroalgal species that blooms periodically in the Yellow Sea of China, has caused the world’s biggest green tide, which induced harmful ecological impacts and economic losses. When the alga is subject to prolonged exposure to air, it suffers abiotic stresses. To explore the physiological and molecular mechanisms of salt stress, the transcriptome data of U. prolifera at different salinities (30, 50, and 90 psu) were obtained by high-throughput sequencing using the Illumina HiSeq platform, and photosynthetic physiological parameters were also measured. The results showed that a total of 89,626 unigenes were obtained after de novo assembly, of which 60,441 unigenes were annotated in the databases (NR, NT, KO, SWISS-PROT, PFAM, GO, and KOG). GO functional enrichment analysis revealed that the enrichment of differentially expressed genes (DEGs) was mainly in cellular, cell, and binding processes. KEGG metabolic pathway enrichment analysis showed that the most frequently enriched pathways of DEGs included glycolysis, pyruvate metabolism, peroxisome, and fatty acid biosynthesis. In addition, resistance-associated proteins, such as heat-shock proteins, microtubule-associated proteins, ubiquitin-associated proteins, abscisic-acid-signaling-pathway-associated proteins, and antioxidant-related proteins are upregulated under salt stress. Genes associated with photosynthesis and carbon fixation pathways are also upregulated, accompanied by an increase in photosynthetic oxygen release rates. These findings provide a basis for understanding the molecular mechanisms of the response of U. prolifera to salinity change, thus providing a theoretical basis for the analysis of the green tide outbreak mechanism.
A Dual Representation Framework for Robot Learning with Human Guidance

: The ability to interactively learn skills from human guidance and adjust behavior according to human preference is crucial to accelerating robot learning. But human guidance is an expensive resource, calling for methods that can learn efﬁciently. In this work, we argue that learning is more efﬁcient if the agent is equipped with a high-level, symbolic representation. We propose a dual representation framework for robot learning from human guidance. The dual representation used by the robotic agent includes one for learning a sensorimotor control policy, and the other, in the form of a symbolic scene graph, for encoding the task-relevant information that motivates human input. We propose two novel learning algorithms based on this framework for learning from human evaluative feedback and from preference. In ﬁve continuous control tasks in simulation and in the real world, we demonstrate that our algorithms lead to signiﬁcant improvement in task performance and learning speed. Additionally, these algorithms require less human effort and are qualitatively preferred by users. Project website: https://sites.google. com/view/dr-hrl .
INFERENCE AND MISSING DATA

Two results are presented concerning inference when data may be missing. First, ignoring the process that causes missing data when making sampling distribution inferences about the parameter of the data, θ, is generally appropriate if and only if the missing data are “missing at random” and the observed data are “observed at random,” and then such inferences are generally conditional on the observed pattern of missing data. Second, ignoring the process that causes missing data when making Bayesian inferences about θ is generally appropriate if and only if the missing data are missing at random and the parameter of the missing data is “independent” of θ. Examples and discussion indicating the implications of these results are included.
Predicting Entropy Generation Rates in Transitional Boundary Layers Based on Intermittency

Prediction of thermodynamic loss in transitional boundary layers is typically based on time-averaged data only. This approach effectively ignores the intermittent nature of the transition region. In this work laminar and turbulent conditionally sampled boundary layer data for zero pressure gradient and accelerating transitional boundary layers have been analyzed to calculate the entropy generation rate in the transition region. By weighting the nondimensional dissipation coefficient for the laminar conditioned data and turbulent conditioned data with the intermittency factor, the entropy generation rate in the transition region can be determined and compared to the time-averaged data and correlations for laminar and turbulent flow. It is demonstrated that this method provides an accurate and detailed picture of the entropy generation rate during transition in contrast with simple time averaging. The data used in this paper have been taken from conditionally sampled boundary layer measurements available in the literature for favorable pressure gradient flows. Based on these measurements, a semi-empirical technique is developed to predict the entropy generation rate in a transitional boundary layer with promising results.
Classical and Quantum Dynamics of Free Electromagnetic Laser Pulses

We discuss the use of a class of exact nite energy solutions to the vacuum source free Maxwell equations as models for multi- and single cycle laser pulses in classical interaction with relativistic charged point particles. These solutions are classied in terms of their chiral content and their inuence on particular charge congurations in space.
Pattern-Mixture Models for Multivariate Incomplete Data

Consider a random sample on variables X1, …, Xv with some values of Xv missing. Selection models specify the distribution of X1 , …, XV over respondents and nonrespondents to Xv , and the conditional distribution that Xv is missing given X1 , …, Xv . In contrast, pattern-mixture models specify the conditional distribution of X 1, …, Xv given that XV is observed or missing respectively and the marginal distribution of the binary indicator for whether or not Xv is missing. For multivariate data with a general pattern of missing values, the literature has tended to adopt the selection-modeling approach (see for example Little and Rubin); here, pattern-mixture models are proposed for this more general problem. Pattern-mixture models are chronically underidentified; in particular for the case of univariate nonresponse mentioned above, there are no data on the distribution of Xv given X1 , …, XV–1 , in the stratum with Xv missing. Thus the models require restrictions or prior information to identify the paramet.
The stability of time-split numerical methods for the hydrostatic and the nonhydrostatic elastic equations

Abstract The mathematical equivalence of the linearized two-dimensional (2D) shallow-water system and the 2D acoustic-advection system strongly suggests that time-split schemes designed for the hydrostatic equations can be employed in nonhydrostatic models and vice versa. Stability analyses are presented for several time-split numerical methods for integrating the two systems. The primary interest is in the nonhydrostatic system and in explicit numerical schemes where no multidimensional elliptic equations arise; thus, a detailed analysis of the Klemp and Wilhelmson (KW) explicit technique for integrating the time-split nonhydrostatic system is undertaken. It is found that the interaction between propagating and advecting acoustic modes can introduce severe constraints on the maximum allowable time steps. Proper filtering can remove these constraints. Other explicit time-split schemes are analysed, and, of all the explicit schemes considered, it is believed that the KW time-split method offers the best co.
Galaxy clusters and the COBE result

The galaxy cluster temperature distribution function is calculated for several primordial power spectra, normalized to the amplitude of the COBE cosmic microwave background fluctuations. Using the Press-Schechter theory, we confirm that the standard cold dark matter model overproduces the abundance of X-ray clusters with this normalization (b∼1 in this case). Three possible resolutions are explored: (1) increasing the large-scale power of a CDM-dominated universe by changing the primeval power spectrum, (2) introducing models with a mixture of hot (∼30%) and cold dark matter, and (3) adopting a flat, low-density model (Ω=0.2, Λ=0.8)
An Acceleration System for Water Drops

Abstract Linear accelerator systems are described which allow the production of series of homogeneously sized water drops of different diameter and at terminal velocity, with small oscillations, negligible charges, and in air of low turbulence intensity. Combinations of parallel systems and blowers displacing the smaller drops into the path of the larger ones allow the study of collision and breakup under conditions which essentially duplicate nature. The chances to observe interactions are considerably enhanced by opto-electronic selection devices.
Resonator frequency shift due to ultrasonically induced microparticle migration in an aqueous suspension: Observations and model for the maximum frequency shift

Aqueous suspensions of plastic and hollow-glass microspheres are subjected to the radiation pressure of an ultrasonic standing wave. It is well known that the particles are attracted to the pressure nodes of the standing wave for the particle and host properties considered. We demonstrated that the radiation pressure induced migration of particles leads to a significant shift in the resonant frequency of a suitably designed chamber. This shift is easily resolved with a phase-locked loop even if the particle volume fraction is as small as 0.001. For sufficient ultrasonic amplitudes, the shift is found to saturate at a limiting value. To approximate the limiting frequency shift, the principle of adiabatic invariance is first applied to the case of a single compressible sphere in a standing wave and then superposition is used to give the collective shift for the suspension. The measured limiting shifts are typically within 25% of the calculated value and this method may have application to the characterizati.
Realistic Numerical Simulations of Solar Convection and Oscillations in Magnetic Regions

We have used 3D, compressible, nonlinear radiative magnetohydrodynamics simulation to study the influence of magnetic fields of various strengths on convective cells and on the excitation mechanisms of acoustic oscillations by calculating the spectral properties of the convective motions and oscillations. The results reveal substantial changes of the granulation structure with increased magnetic field and a frequency-dependent reduction in the oscillation power in a good agreement with solar observations. These simulations suggest that the enhanced high-frequency acoustic emission at the boundaries of active regions (“acoustic halo” phenomenon) is caused by changes of the spatial-temporal spectrum of turbulent convection in a magnetic field, resulting in turbulent motions of smaller scales and higher frequencies than in quiet-Sun regions.
The global assimilation of information for action (GAIA) initiative: understanding the impact of climate change on national security and public health

Global Assimilation of Information for Action (GAIA) is a new initiative at The Johns Hopkins University connecting decision-makers with the research community. GAIA's focus is on the near- and long-term effects of weather, climate, and climate disruption on society and national security. The GAIA initiative, http://gaia.jhuapl. edu, makes use of collaborative tools to bring together decision makers to address focused problems in settings that range from symposia and workshops to specific socio-political-economic "games" to explore how decisions can be made and risks assessed. GAIA includes a suite of visualization tools, documentation, analyses, and social networking capabilities. Here, we will discuss the GAIA collaboration and recent GAIA projects, in particular the development of climate change national security gaming scenarios and studies in public health, and how the GAIA project can aide in assessing national security and public health concerns.
The effects of additive outliers on the seasonal KPSS test: a Monte Carlo analysis

This article builds on the test proposed by Lyhagen [The seasonal KPSS statistic, Econom. Bull. 3 (2006), pp. 1–9] for seasonal time series and having the null hypothesis of level stationarity against the alternative of unit root behaviour at some or all of the zero and seasonal frequencies. This new test is qualified as seasonal-frequency Kwiatkowski–Phillips–Schmidt–Shin (KPSS) test and it is not originally supported by a regression framework. The purpose of this paper is twofold. Firstly, we propose a model-based regression method and provide a clear illustration of Lyhagen's test and we establish its asymptotic theory in the time domain. Secondly, we use the Monte Carlo method to study the finite-sample performance of the seasonal KPSS test in the presence of additive outliers. Our simulation analysis shows that this test is robust to the magnitude and the number of outliers and the statistical results obtained cast an overall good performance of the test finite-sample properties.
Spin splitting of the electron ground states of InAs quantum dots

Here, we present results on the spin splitting of electrons in the ground state of InAs self-assembled quantum dots (QDs). The spin splitting is assessed by capacitance spectroscopy, which allows direct measurement of the electronic g-factor modulus. By applying the magnetic field parallel to the [001], [110], and [110] crystallographic directions, we found that for magnetic fields below 5 T the g factor depends on the orientation, reflecting the QD anisotropy. For higher fields, the g factor does not exhibit the same degree of anisotropy, indicating a compression of the wave function inside the QD along the [001] direction, and consequently, a dependence on the magnitude of the applied field.
Closure theorems for spaces of entire functions

The purpose of this department is to provide early announcement of new results of such immediate importance to a substantial set of mathematicians that their communication to the mathematical community cannot await the normal time of publication. Research Announcements are communicated to the Bulletin by members of the Publications Committees listed on the inside back cover; manuscripts should be sent directly to any one of them. Each communicator is limited to accepting not more than six announcements each year; announcements are limited to 100 typed lines of 65 spaces each. CLOSURE THEOREMS FOR SPACES OF ENTIRE FUNCTIONS BY LOREN D. PITT
Analysis and design using the allowable eigenvector subspace

Abstract Eigenstructure assignment has enjoyed considerable success in applications where both the modal response and mode distribution are important. However, a significant constraint on eigenvector selection is defined by an allowable subspace, the range of which varies both with model parameters and desired eigenvalue. This paper presents a technique that explores this constraint, from which analysis and design methods result. A four-input, eighth-order helicopter model is presented. The application of the novel method reveals the achievable response rates in the helicopter states, and provides information on how parameter variations affect the system dynamics. A revised eigenstructure is developed, and the resulting closed-loop system is shown to comply with handling qualities specifications while reducing cross-coupling between modes.
Enzyme-based lactic acid detection using AlGaN /GaN high electron mobility transistors with ZnO nanorods grown on the gate region

The detection of lactic acid with ZnO nanorod-gated AlGaN∕GaN high electron mobility transistors (HEMTs) was demonstrated. The array of ZnO nanorods provided a large effective surface area with a high surface-to-volume ratio and a favorable environment for the immobilization of lactate oxidase. The HEMT drain-source current showed a rapid response when various concentrations of lactic acid solutions were introduced to the gate area of the HEMT sensor. The HEMT could detect lactic acid concentrations from 167nM to 139μM. Our results show that portable, fast response, and wireless-based lactic acid detectors can be realized with AlGaN∕GaN HEMT based sensors.
Rapid scatter estimation for CBCT using the Boltzmann transport equation

Scatter in cone-beam computed tomography (CBCT) is a significant problem that degrades image contrast, uniformity and CT number accuracy. One means of estimating and correcting for detected scatter is through an iterative deconvolution process known as scatter kernel superposition (SKS). While the SKS approach is efficient, clinically significant errors on the order 2-4% (20-40 HU) still remain. We have previously shown that the kernel method can be improved by perturbing the kernel parameters based on reference data provided by limited Monte Carlo simulations of a first-pass reconstruction. In this work, we replace the Monte Carlo modeling with a deterministic Boltzmann solver (AcurosCTS) to generate the reference scatter data in a dramatically reduced time. In addition, the algorithm is improved so that instead of adjusting kernel parameters, we directly perturb the SKS scatter estimates. Studies were conducted on simulated data and on a large pelvis phantom scanned on a tabletop system. The new method reduced average reconstruction errors (relative to a reference scan) from 2.5% to 1.8%, and significantly improved visualization of low contrast objects. In total, 24 projections were simulated with an AcurosCTS execution time of 22 sec/projection using an 8-core computer. We have ported AcurosCTS to the GPU, and current run-times are approximately 4 sec/projection using two GPU’s running in parallel.
Spectroscopic investigation of highly transient pinch plasmas

The temporal evolution of neon pinch plasmas, generated in a 2 kJ plasma focus device, has been investigated by x-ray spectroscopic methods for two sets of device parameters. These two sets lead to characteristic differences of the K-shell emission. Stationary models are shown to fail to explain the experimental observations even qualitatively. Transient spectra analysis shows that the characteristic differences observed can be referred to different transient modes of plasma dynamics. The spectra analysis includes beside resonance lines also dielectronic satellites and recombination continua. The results concerning the development of the plasma parameters achieved by the spectra modeling are supported by independent measurements of the time resolved K-shell emission and by optical streak images of the pinch plasma dynamics, which confirms the reliability of the transient spectroscopic analysis presented. {copyright} {ital 1997} {ital The American Physical Society}