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Current and upcoming generations of visible-shortwave infrared (VSWIR) imaging spectrometers promise unprecedented capacity to quantify Earth System processes across the globe. However, reliable cloud screening remains a fundamental challenge for these instruments, where traditional spatial and temporal approaches are limited by cloud variability and limited temporal coverage. The Spectroscopic Transformer (SpecTf) addresses these challenges with a spectroscopy-specific deep learning architecture that performs cloud detection using only spectral information (no spatial or temporal data are required). By treating spectral measurements as sequences rather than image channels, SpecTf learns fundamental physical relationships without relying on spatial context. Our experiments demonstrate that SpecTf significantly outperforms the current baseline approach implemented for the EMIT instrument, and performs comparably with other machine learning methods with orders of magnitude fewer learned parameters. Critically, we demonstrate SpecTf's inherent interpretability through its attention mechanism, revealing physically meaningful spectral features the model has learned. Finally, we present SpecTf's potential for cross-instrument generalization by applying it to a different instrument on a different platform without modifications, opening the door to instrument agnostic data driven algorithms for future imaging spectroscopy tasks., Comment: 23 pages, 5 figures, in review. Code repository: https://github.com/emit-sds/SpecTf

Low back pain (LBP) is a leading cause of disability globally. Following the onset of LBP and subsequent treatment, adequate patient education is crucial for improving functionality and long-term outcomes. Despite advancements in patient education strategies, significant gaps persist in delivering personalized, evidence-based information to patients with LBP. Recent advancements in large language models (LLMs) and generative artificial intelligence (GenAI) have demonstrated the potential to enhance patient education. However, their application and efficacy in delivering educational content to patients with LBP remain underexplored and warrant further investigation. In this study, we introduce a novel approach utilizing LLMs with Retrieval-Augmented Generation (RAG) and few-shot learning to generate tailored educational materials for patients with LBP. Physical therapists manually evaluated our model responses for redundancy, accuracy, and completeness using a Likert scale. In addition, the readability of the generated education materials is assessed using the Flesch Reading Ease score. The findings demonstrate that RAG-based LLMs outperform traditional LLMs, providing more accurate, complete, and readable patient education materials with less redundancy. Having said that, our analysis reveals that the generated materials are not yet ready for use in clinical practice. This study underscores the potential of AI-driven models utilizing RAG to improve patient education for LBP; however, significant challenges remain in ensuring the clinical relevance and granularity of content generated by these models.

The Large Binocular Telescope, with its expansive collecting area, angular resolving power, and advanced optical design, provides a robust platform for development and operation of advanced instrumentation for astronomical research. The LBT currently hosts a mature suite of instruments for spectroscopy and imaging at optical through mid-infrared wavelengths, supported by sophisticated adaptive optics systems. This contribution summarizes the current state of instrumentation, including upgrades to existing instruments and commissioning of second generation instruments now in progress. The LBT is soliciting proposals for next generation instrument concepts, with participation open to consortium members and others interested in participation in the Observatory., Comment: 6 pages, Proc. SPIE 13096-4, Ground-based and Airborne Instrumentation for Astronomy X, Yokohama 2024

Planetary rovers can use onboard data analysis to adapt their measurement plan on the fly, improving the science value of data collected between commands from Earth. This paper describes the implementation of an adaptive sampling algorithm used by PIXL, the X-ray fluorescence spectrometer of the Mars 2020 Perseverance rover. PIXL is deployed using the rover arm to measure X-ray spectra of rocks with a scan density of several thousand points over an area of typically 5 x 7 mm. The adaptive sampling algorithm is programmed to recognize points of interest and to increase the signal-to-noise ratio at those locations by performing longer integrations. Two approaches are used to formulate the sampling rules based on past quantification data: 1) Expressions that isolate particular regions within a ternary compositional diagram, and 2) Machine learning rules that threshold for a high weight percent of particular compounds. The design of the rulesets are outlined and the performance of the algorithm is quantified using measurements from the surface of Mars. To our knowledge, PIXL's adaptive sampling represents the first autonomous decision-making based on real-time compositional analysis by a spacecraft on the surface of another planet., Comment: 24 pages including 11 figures and 7 tables. Submitted for publication to the journal Icarus

At speeds above 300 km/h, aerodynamic noise becomes a significant source of railway noise. In a high-speed train, the bogie area is one of the most important aerodynamic noise sources. To predict aerodynamic noise, semi-empirical component-based models are attractive as they allow fast and cheap calculations compared with numerical methods. Such component-based models have been previously applied successfully to predict the aerodynamic noise from train pantographs which consist of various cylinders. In this work, the feasibility is evaluated of applying them to the aerodynamic noise from bogies, which consist of various bluff bodies. To this end, noise measurements were carried out in an anechoic wind tunnel for different flow speeds using simple shapes representing various idealised components of a bogie. These results have been used to adjust the empirical constants of the component-based prediction model to enable its application to the bogie case. In addition, the noise from a 1:10 scale simplified bogie mock-up was measured and used for comparison with the prediction model. The results show good agreement between measurements and predictions for the bogie alone. When the bogie is located between two ramps approximating a simplified bogie cavity the noise is underpredicted at low frequencies. This is attributed to the noise from the cavity which is not included in the model.

The joint retrieval of surface reflectances and atmospheric parameters in VSWIR imaging spectroscopy is a computationally challenging high-dimensional problem. Using NASA's Surface Biology and Geology mission as the motivational context, the uncertainty associated with the retrievals is crucial for further application of the retrieved results for environmental applications. Although Markov chain Monte Carlo (MCMC) is a Bayesian method ideal for uncertainty quantification, the full-dimensional implementation of MCMC for the retrieval is computationally intractable. In this work, we developed a block Metropolis MCMC algorithm for the high-dimensional VSWIR surface reflectance retrieval that leverages the structure of the forward radiative transfer model to enable tractable fully Bayesian computation. We use the posterior distribution from this MCMC algorithm to assess the limitations of optimal estimation, the state-of-the-art Bayesian algorithm in operational retrievals which is more computationally efficient but uses a Gaussian approximation to characterize the posterior. Analyzing the differences in the posterior computed by each method, the MCMC algorithm was shown to give more physically sensible results and reveals the non-Gaussian structure of the posterior, specifically in the atmospheric aerosol optical depth parameter and the low-wavelength surface reflectances.

We present 294 pulsars found in GeV data from the Large Area Telescope (LAT) on the Fermi Gamma-ray Space Telescope. Another 33 millisecond pulsars (MSPs) discovered in deep radio searches of LAT sources will likely reveal pulsations once phase-connected rotation ephemerides are achieved. A further dozen optical and/or X-ray binary systems co-located with LAT sources also likely harbor gamma-ray MSPs. This catalog thus reports roughly 340 gamma-ray pulsars and candidates, 10% of all known pulsars, compared to $\leq 11$ known before Fermi. Half of the gamma-ray pulsars are young. Of these, the half that are undetected in radio have a broader Galactic latitude distribution than the young radio-loud pulsars. The others are MSPs, with 6 undetected in radio. Overall, >235 are bright enough above 50 MeV to fit the pulse profile, the energy spectrum, or both. For the common two-peaked profiles, the gamma-ray peak closest to the magnetic pole crossing generally has a softer spectrum. The spectral energy distributions tend to narrow as the spindown power $\dot E$ decreases to its observed minimum near $10^{33}$ erg s$^{-1}$, approaching the shape for synchrotron radiation from monoenergetic electrons. We calculate gamma-ray luminosities when distances are available. Our all-sky gamma-ray sensitivity map is useful for population syntheses. The electronic catalog version provides gamma-ray pulsar ephemerides, properties and fit results to guide and be compared with modeling results., Comment: 142 pages. Accepted by the Astrophysical Journal Supplement

For tidal energy to become an alternative energy resource to fossil fuels then there needs to be confidence in the predicted performance of horizontal axis tidal turbine devices. A number of computational fluids dynamics packages are now available to assist in the design and testing of new devices. The work in this paper describes a comparative study as a scoping exercise between two widely used packages, OpenFOAM and ANSYS CFX. The numerical simulations were run using the same geometry, mesh and turbulence model on both software. The results were compared to experimental testing conducted at INSEAN. The setup for each model is detailed. Differences were noted in the running and setup of the models as well as within the time history of the results. Overall both CFX and OpenFOAM were shown to give good predictions for the performance coefficients compared to the experimental testing with the data averaged over several complete rotations and well when compared to each other.

Vanderweele and Knol define biological interaction as an instance wherein "two exposures physically interact to bring about the outcome." A hallmark of biological interaction is that the total effect, produced when factors act together, differs from the sum of effects when the factors operate independently. Epidemiologists construct statistical models to assess biological interaction. The form of the statistical model determines whether it is suited to detecting departures from additivity of effects or for detecting departures from multiplicativity of effects. A consensus exists that biological interaction should be assessed as a departure from additivity of effects. This paper compares three statistical models' assessment of a data example that appears in several epidemiology textbooks to illustrate biological interaction in a binomial outcome. A linear binomial model quantifies departure from additivity in the data example in terms of differences in probabilities. It generates directly interpretable estimates and 95% confidence intervals for parameters including the interaction contrast (IC). Log binomial and logistic regression models detect no departure from multiplicativity in the data example. However, their estimates contribute to calculation of a "Relative Excess Risk Due to Interaction" (RERI), a measure of departure from additivity on a relative risk scale. The linear binomial model directly produces interpretable assessments of departures from additivity of effects and deserves wider use in research and in the teaching of epidemiology. Strategies exist to address the model's limitations., Comment: 29 pages, 3 tables, 3 figures

Electron-positron pair production is the essential process for high-energy gamma-ray astrophysical observations. Following the pioneering OSO-3 counter telescope, the field evolved into use of particle tracking instruments, largely derived from high-energy physics detectors. Although many of the techniques were developed on balloon-borne gamma-ray telescopes, the need to escape the high background in the atmosphere meant that the breakthrough discoveries came from the SAS-2 and COS-B satellites. The next major pair production success was EGRET on the Compton Gamma Ray Observatory, which provided the first all-sky map at energies above 100 MeV and found a variety of gamma-ray sources, many of which were variable. The current generation of pair production telescopes, AGILE and Fermi LAT, have broadened high-energy gamma-ray astrophysics with particular emphasis on multiwavelength and multimessenger studies. A variety of options remain open for future missions based on pair production with improved instrumental performance., Comment: 35 pages, 17 figures, To appear in "Handbook of X-ray and Gamma-ray Astrophysics" by Springer - Editors in chief: C. Bambi and A. Santangelo

The Fermi Gamma-ray Space Telescope, a key mission in multiwavelength and multimessenger studies, has been surveying the gamma-ray sky from its low-Earth orbit since 2008. Its two scientific instruments, the Gamma-ray Burst Monitor (GBM) and the Large Area Telescope (LAT), cover 8 orders of magnitude in photon energy. The GBM consists of 12 Sodium Iodide detectors and 2 Bismuth Germinate detectors, covering the 10 keV - 40 MeV energy range, arrayed on two sides of the spacecraft so as to view the entire sky that is not occulted by the Earth. The LAT is a pair production telescope based on silicon strip trackers, a Cesium Iodide calorimeter, and a plastic scintillator anticoincidence system. It covers the energy range from about 20 MeV to more than 500 GeV, with a field of view of about 2.4 steradians. Thanks to their huge fields of view, the instruments can observe the entire sky with a cadence of about an hour for GBM and about three hours for LAT. All gamma-ray data from Fermi become public immediately, enabling a broad range of multiwavelength and multimessenger research. Over 3000 gamma-ray bursts (GRBs), including GRB 170817A associated with a neutron star merger detected in gravitational waves, and 5000 high-energy sources, including the blazar TXS 0506+056 associated with high-energy neutrinos, have been detected by the Fermi instruments. The Fermi Science Support Center provides a wide array of resources to enable scientific use of the data, including background models, source catalogs, analysis software, documentation, and a Help Desk., Comment: 36 pages, 13 figures. To appear in "Handbook of X-ray and Gamma-ray Astrophysics" by Springer - Editors in chief: C. Bambi and A. Santangelo

Sturm's Theorem is a fundamental 19th century result relating the number of real roots of a polynomial $f$ in an interval to the number of sign alternations in a sequence of polynomial division-like calculations. We provide a short direct proof of Sturm's Theorem, including the numerically vexing case (ignored in many published accounts) where an interval endpoint is a root of $f$., Comment: 4 pages. A software implementation can be found in algorithm vtkPolynomialSolversUnivariate , within the VTK (Visualization Toolkit) software package

We present an incremental version (4FGL-DR3, for Data Release 3) of the fourth Fermi-LAT catalog of gamma-ray sources. Based on the first twelve years of science data in the energy range from 50 MeV to 1 TeV, it contains 6658 sources. The analysis improves on that used for the 4FGL catalog over eight years of data: more sources are fit with curved spectra, we introduce a more robust spectral parameterization for pulsars, and we extend the spectral points to 1 TeV. The spectral parameters, spectral energy distributions, and associations are updated for all sources. Light curves are rebuilt for all sources with 1 yr intervals (not 2 month intervals). Among the 5064 original 4FGL sources, 16 were deleted, 112 are formally below the detection threshold over 12 yr (but are kept in the list), while 74 are newly associated, 10 have an improved association, and seven associations were withdrawn. Pulsars are split explicitly between young and millisecond pulsars. Pulsars and binaries newly detected in LAT sources, as well as more than 100 newly classified blazars, are reported. We add three extended sources and 1607 new point sources, mostly just above the detection threshold, among which eight are considered identified, and 699 have a plausible counterpart at other wavelengths. We discuss degree-scale residuals to the global sky model and clusters of soft unassociated point sources close to the Galactic plane, which are possibly related to limitations of the interstellar emission model and missing extended sources., Comment: accepted in ApJS; follow-up paper to 1902.10045

The sky at MeV energies is currently poorly explored. Here we present an innovative mission concept that builds on and improves past and currently proposed missions at such energies. We outline the motivations for combining a coded mask and a Compton telescope and we define the scientific goals of such a mission. The Galactic Explorer with a Coded Aperture Mask Compton Telescope (GECCO) is a novel concept for a next-generation telescope covering hard X-ray and soft gamma-ray energies. The potential and importance of this approach that bridges the observational gap in the MeV energy range are presented. With the unprecedented angular resolution of the coded mask telescope combined with the sensitive Compton telescope, a mission such as GECCO can disentangle the discrete sources from the truly diffuse emission. Individual Galactic and extragalactic sources are detected. This also allows to understand the gamma-ray Galactic center excess and the Fermi Bubbles, and to trace the low-energy cosmic rays, and their propagation in the Galaxy. Nuclear and annihilation lines are spatially and spectrally resolved from the continuum emission and from sources, addressing the role of low-energy cosmic rays in star formation and galaxy evolution, the origin of the 511 keV positron line, fundamental physics, and the chemical enrichment in the Galaxy. Such an instrument also detects explosive transient gamma-ray sources, which enable identifying and studying the astrophysical objects that produce gravitational waves and neutrinos in a multi-messenger context. By looking at a poorly explored energy band it also allows discoveries of new astrophysical phenomena., Comment: 16 pages. Contact authors: Elena Orlando, Eugenio Bottacini

Little is known about Earth quasi-satellites, a class of near-Earth small solar system bodies that orbit the sun but remain close to the Earth, because they are faint and difficult to observe. Here we use the Large Binocular Telescope (LBT) and the Lowell Discovery Telescope (LDT) to conduct a comprehensive physical characterization of quasi-satellite (469219) Kamo`oalewa and assess its affinity with other groups of near-Earth objects. We find that (469219) Kamo`oalewa rotates with a period of 28.3 (+1.8/-1.3) minutes and displays a reddened reflectance spectrum from 0.4-2.2 microns. This spectrum is indicative of a silicate-based composition, but with reddening beyond what is typically seen amongst asteroids in the inner solar system. We compare the spectrum to those of several material analogs and conclude that the best match is with lunar-like silicates. This interpretation implies extensive space weathering and raises the prospect that Kamo`oalewa could comprise lunar material., Comment: Published in Nature Communications Earth and Environment

Three statistical studies, all published between 2004 and 2008 but without referring to one another, assert a useful equivalence involving the hazard ratio, a parameter estimated for time to event data by the frequently used proportional hazards model. Stated generally, when the assumption of proportional hazards is justified, the hazard ratio is equivalent to the odds that a randomly chosen person from the group whose hazard is represented in the ratio's numerator will experience the event of interest before a randomly chosen person from the group represented by the ratio's denominator., Comment: 4 pages including mathematical derivation

High sensitivity radio searches of unassociated $\gamma$-ray sources have proven to be an effective way of finding new pulsars. Using the Five-hundred-meter Aperture Spherical radio Telescope (FAST) during its commissioning phase, we have carried out a number of targeted deep searches of \textit{Fermi} Large Area Telescope (LAT) $\gamma$-ray sources. On Feb. 27$^{th}$, 2018 we discovered an isolated millisecond pulsar (MSP), PSR J0318+0253, coincident with the unassociated $\gamma$-ray source 3FGL J0318.1+0252. PSR J0318+0253 has a spin period of $5.19$ milliseconds, a dispersion measure (DM) of $26$ pc cm$^{-3}$ corresponding to a DM distance of about $1.3$ kpc, and a period-averaged flux density of $\sim$11 $\pm$ 2 $\mu$Jy at L-band (1.05-1.45 GHz). Among all high energy MSPs, PSR J0318+0253 is the faintest ever detected in radio bands, by a factor of at least $\sim$4 in terms of L-band fluxes. With the aid of the radio ephemeris, an analysis of 9.6 years of \textit{Fermi}-LAT data revealed that PSR J0318+0253 also displays strong $\gamma$-ray pulsations. Follow-up observations carried out by both Arecibo and FAST suggest a likely spectral turn-over around 350 MHz. This is the first result from the collaboration between FAST and the \textit{Fermi}-LAT teams as well as the first confirmed new MSP discovery by FAST, raising hopes for the detection of many more MSPs. Such discoveries will make a significant contribution to our understanding of the neutron star zoo while potentially contributing to the future detection of gravitational waves, via pulsar timing array (PTA) experiments., Comment: 7 pages, 2 figures, 1 table

Matched filter (MF) techniques have been widely used for retrieval of greenhouse gas enhancements (enh.) from imaging spectroscopy datasets. While multiple algorithmic techniques and refinements have been proposed, the greenhouse gas target spectrum used for concentration enh. estimation has remained largely unaltered since the introduction of quantitative MF retrievals. The magnitude of retrieved methane and carbon dioxide enh., and thereby integrated mass enh. (IME) and estimated flux of point-source emitters, is heavily dependent on this target spectrum. Current standard use of molecular absorption coefficients to create unit enh. target spectra does not account for absorption by background concentrations of greenhouse gases, solar and sensor geometry, or atmospheric water vapor absorption. We introduce geometric and atmospheric parameters into the generation of scene-specific (SS) unit enh. spectra to provide target spectra that are compatible with all greenhouse gas retrieval MF techniques. For methane plumes, IME resulting from use of standard, generic enh. spectra varied from -22 to +28.7% compared to SS enh. spectra. Due to differences in spectral shape between the generic and SS enh. spectra, differences in methane plume IME were linked to surface spectral characteristics in addition to geometric and atmospheric parameters. IME differences for carbon dioxide plumes, with generic enh. spectra producing integrated mass enh. -76.1 to -48.1% compared to SS enh. spectra. Fluxes calculated from these integrated enh. would vary by the same %s, assuming equivalent wind conditions. Methane and carbon dioxide IME were most sensitive to changes in solar zenith angle and ground elevation. SS target spectra can improve confidence in greenhouse gas retrievals and flux estimates across collections of scenes with diverse geometric and atmospheric conditions., Comment: 13 pages, 5 figures, 3 tables

When observations are independent, formulae and software are readily available to plan and design studies of appropriate size and power to detect important associations. When observations are correlated or clustered, results obtained from the standard software require adjustment. This tutorial compares two approaches, using examples that illustrate various designs for both independent and clustered data. One approach obtains initial estimates using software that assume independence among observations, then adjusts these estimates using a design effect (DE), also called a variance inflation factor (VIF). A second approach generates estimates using generalized linear mixed models (GLMM) that account directly for patterns of clustering and correlation. The two approaches generally produce similar estimates and so validate one another. For certain clustered designs, small differences in power estimates emphasize the importance of specifying an alternative hypothesis in terms of means but also in terms of expected variances and covariances. Both approaches to power estimation are sensitive to assumptions concerning the structure or pattern of independence or correlation among clustered outcomes., Comment: 43 pages, 3 figures, 2 tables Article replaced on 3-12-2021 to include less restrictive, more general SAS syntax on pages 6 and 40; results unchanged

Affective brain-computer interfaces are a relatively new area of research in affective computing. Estimation of affective states can improve human-computer interaction as well as improve the care of people with severe disabilities. To assess the effectiveness of EEG recordings in recognizing affective state, here we used data collected in our lab as well as the publicly available DEAP database. We also reviewed the articles that used the DEAP database and found that a significant number of articles did not consider the presence of the class imbalance in the DEAP. Failing to consider class imbalance creates misleading results. Further, ignoring class imbalance makes the comparing results between studies impossible, since different datasets will have different class imbalances. Class imbalance also shifts the chance level, hence it is vital to consider class bias while determining if the results are above chance. To properly account the effect of class imbalance, we suggest the use of balanced accuracy as a performance metric and its posterior distribution for computing credible intervals. For classification, we used features mentioned in the literature and additionally theta beta-1 ratio. Results from DEAP and our data suggest that the beta band power, theta band power, and theta beta-1 ratio are better feature sets for classifying valence, arousal, and dominance, respectively., Comment: 12 pages, 4 figures, 2 tables

The strong radiative forcing by atmospheric methane has stimulated interest in identifying natural and anthropogenic sources of this potent greenhouse gas. Point sources are important targets for quantification, and anthropogenic targets have potential for emissions reduction. Methane point source plume detection and concentration retrieval have been previously demonstrated using data from the Airborne Visible InfraRed Imaging Spectrometer Next Generation (AVIRIS-NG). Current quantitative methods have tradeoffs between computational requirements and retrieval accuracy, creating obstacles for processing real-time data or large datasets from flight campaigns. We present a new computationally efficient algorithm that applies sparsity and an albedo correction to matched filter retrieval of trace gas concentration-pathlength. The new algorithm was tested using AVIRIS-NG data acquired over several point source plumes in Ahmedabad, India. The algorithm was validated using simulated AVIRIS-NG data including synthetic plumes of known methane concentration. Sparsity and albedo correction together reduced the root mean squared error of retrieved methane concentration-pathlength enhancement by 60.7% compared with a previous robust matched filter method. Background noise was reduced by a factor of 2.64. The new algorithm was able to process the entire 300 flightline 2016 AVIRIS-NG India campaign in just over 8 hours on a desktop computer with GPU acceleration., Comment: 13 pages, 11 figures

The All-sky Medium Energy Gamma-ray Observatory (AMEGO) is a probe class mission concept that will provide essential contributions to multimessenger astrophysics in the late 2020s and beyond. AMEGO combines high sensitivity in the 200 keV to 10 GeV energy range with a wide field of view, good spectral resolution, and polarization sensitivity. Therefore, AMEGO is key in the study of multimessenger astrophysical objects that have unique signatures in the gamma-ray regime, such as neutron star mergers, supernovae, and flaring active galactic nuclei. The order-of-magnitude improvement compared to previous MeV missions also enables discoveries of a wide range of phenomena whose energy output peaks in the relatively unexplored medium-energy gamma-ray band., Comment: Astro2020 APC White Paper Updated to make small change to author list in metadata

According to a recent investigation, an estimated 33-50% of the world's coral reefs have undergone degradation, believed to be as a result of climate change. A strong driver of climate change and the subsequent environmental impact are greenhouse gases such as methane. However, the exact relation climate change has to the environmental condition cannot be easily established. Remote sensing methods are increasingly being used to quantify and draw connections between rapidly changing climatic conditions and environmental impact. A crucial part of this analysis is processing spectroscopy data using radiative transfer models (RTMs) which is a computationally expensive process and limits their use with high volume imaging spectrometers. This work presents an algorithm that can efficiently emulate RTMs using neural networks leading to a multifold speedup in processing time, and yielding multiple downstream benefits., Comment: Accepted to International Conference on Machine Learning (ICML) 2019 Workshop: Climate Change: How Can AI Help?