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This paper introduces SpineFM, a novel pipeline that achieves state-of-the-art performance in the automatic segmentation and identification of vertebral bodies in cervical and lumbar spine radiographs. SpineFM leverages the regular geometry of the spine, employing a novel inductive process to sequentially infer the location of each vertebra along the spinal column. Vertebrae are segmented using Medical-SAM-Adaptor, a robust foundation model that diverges from commonly used CNN-based models. We achieved outstanding results on two publicly available spine X-Ray datasets, with successful identification of 97.8\% and 99.6\% of annotated vertebrae, respectively. Of which, our segmentation reached an average Dice of 0.942 and 0.921, surpassing previous state-of-the-art methods., Comment: 4 pages, 3 figures, submitted to ISBI 2025

We use JWST/NIRISS slitless spectroscopy from the Next Generation Deep Extragalactic Exploratory Public (NGDEEP) Survey to investigate the physical condition of star-forming galaxies at $1.7 < z < 3.4$. At these redshifts, the deep NGDEEP NIRISS slitless spectroscopy covers the [O II]$\lambda\lambda$3726,3729, [O III]$\lambda\lambda$4959,5007, H$\beta$ and H$\alpha$ emission features for galaxies with stellar masses $\log(\mathrm{M_\ast/M_\odot}) \gtrsim 7$, nearly a factor of a hundred lower than previous studies. We focus on the [O III]/[O II] (O$_{32}$) ratio which is primarily sensitive to the ionization state and with a secondary dependence on the gas-phase metallicity of the interstellar medium. We find significant ($\gtrsim5\sigma$) correlations between the O$_{32}$ ratio and galaxy properties as O$_{32}$ increases with decreasing stellar mass, decreasing star formation rate (SFR), increasing specific SFR (sSFR$\equiv \mathrm{SFR}/M_*$), and increasing equivalent width (EW) of H$\beta$ and H$\alpha$. These trends suggest a tight connection between the ionization parameter and these galaxy properties. Galaxies at $z\sim2-3$ exhibit a higher O$_{32}$ than local normal galaxies with the same stellar masses and SFRs, indicating that they have a higher ionization parameter and lower metallicity than local normal galaxies. In addition, we observe an evolutionary trend in the O$_{32}$ -- EW(H$\beta$) relation from $z\sim0$ and $z\gtrsim5$, such that higher redshift galaxies have higher EW(H$\beta$) and higher O$_{32}$ at fixed EW. We argue that both the enhanced recent star formation activity and the higher star formation surface density may contribute to the increase in O$_{32}$ and the ionization parameter., Comment: 27 pages, 14 figures

Rydberg states of alkali atoms are highly sensitive to electromagnetic radiation in the GHz-to-THz regime because their transitions have large electric dipole moments. Consequently, environmental blackbody radiation (BBR) can couple Rydberg states together at $\mu$s timescales. Here, we track the BBR-induced transfer of a prepared Rydberg state to its neighbors and use the evolution of these state populations to characterize the BBR field at the relevant wavelengths, primarily at 130 GHz. We use selective field ionization readout of Rydberg states with principal quantum number $n\sim30$ in $^{85}$Rb and substantiate our ionization signal with a theoretical model. With this detection method, we measure the associated blackbody-radiation-induced time dynamics of these states, reproduce the results with a simple semi-classical population transfer model, and demonstrate that this measurement is temperature sensitive with a statistical sensitivity to the fractional temperature uncertainty of 0.09 Hz$^{-1/2}$, corresponding to 26 K$\cdot$Hz$^{-1/2}$ at room temperature. This represents a calibration-free SI-traceable temperature measurement, for which we calculate a systematic fractional temperature uncertainty of 0.006, corresponding to 2 K at room temperature when used as a primary temperature standard.

JWST spectroscopy has discovered a population of $z \gtrsim 3.5$ galaxies with broad Balmer emission lines, and narrow forbidden lines, that are consistent with hosting active galactic nuclei (AGN). Many of these systems, now known as ``little red dots" (LRDs), are compact and have unique colors that are very red in the optical/near-infrared and blue in the ultraviolet. The relative contribution of galaxy starlight and AGN to these systems remains uncertain, especially for the galaxies with unusual blue+red spectral energy distributions. In this work, we use Balmer decrements to measure the independent dust attenuation of the broad and narrow emission-line components of a sample of 29 broad-line AGN identified from three public JWST spectroscopy surveys: CEERS, JADES, and RUBIES. Stacking the narrow components from the spectra of 25 sources with broad H$\rm{\alpha}$ and no broad H$\rm{\beta}$ results in a median narrow H$\rm{\alpha}$/H$\rm{\beta}$ = $2.47^{+0.05}_{-0.05}$ (consistent with $A_{v} = 0$) and broad H$\rm{\alpha}$/H$\rm{\beta}$ $> 8.85$ ($A_{v} > 3.63$). The narrow and broad Balmer decrements imply little-to-no attenuation of the narrow emission lines, which are consistent with being powered by star formation and located on larger physical scales. Meanwhile, the lower limit in broad H$\rm{\alpha}$/H$\rm{\beta}$ decrement, with broad H$\rm{\beta}$ undetected in the stacked spectrum of 25 broad-H$\rm{\alpha}$ AGN, implies significant dust attenuation of the broad-line emitting region that is presumably associated with the central AGN. Our results indicate that these systems, on average, are consistent with heavily dust-attenuated AGN powering the red parts of their SED while their blue UV emission is powered by unattenuated star formation in the host galaxy., Comment: 4 figures, 3 tables

In this paper, we develop an embodied AI system for human-in-the-loop navigation with a wheeled mobile robot. We propose a direct yet effective method of monitoring the robot's current plan to detect changes in the environment that impact the intended trajectory of the robot significantly and then query a human for feedback. We also develop a means to parse human feedback expressed in natural language into local navigation waypoints and integrate it into a global planning system, by leveraging a map of semantic features and an aligned obstacle map. Extensive testing in simulation and physical hardware experiments with a resource-constrained wheeled robot tasked to navigate in a real-world environment validate the efficacy and robustness of our method. This work can support applications like precision agriculture and construction, where persistent monitoring of the environment provides a human with information about the environment state.

We investigate the co-evolution of the angular momentum of Milky Way-like galaxies, their circumgalactic gas, and their dark matter halos using zoom-in simulations from the Figuring Out Gas & Galaxies in Enzo (FOGGIE) suite. We examine how the magnitude and orientation of the angular momentum varies over time within the halo and between the components of mass. From z~2 to today, and in general across the simulated halos, the specific angular momenta of the central galaxies and the cool gas in their circumgalactic media (T < 10^5 K) increase together. Over that same period, the specific angular momenta of the hot (>10^6 K) and dark components of the halo change minimally. By z~1, the central galaxies have generally lost association with the angular momentum of their full dark matter halo -- both in magnitude and orientation. We find a wide distribution of angular momentum orientations in the halo, varying by up to 180 degrees over small (~tens of kpc) scales and between the different components of mass. The net angular momenta of the galaxies, their circumgalactic gas, and their dark matter halos are generally misaligned with one another at all cosmic times. The present-day orientation of the central galaxies are established at late times (after z=1), after the rates of cosmic accretion and mergers decline and the disks are able to settle and stabilize their orientation., Comment: 35 pages, 14 figures, submitted to ApJ

Water is often overused in irrigation, making efficient management of it crucial. Precision Agriculture emphasizes tools like stem water potential (SWP) analysis for better plant status determination. However, such tools often require labor-intensive in-situ sampling. Automation and machine learning can streamline this process and enhance outcomes. This work focused on automating stem detection and xylem wetness classification using the Scholander Pressure Chamber, a widely used but demanding method for SWP measurement. The aim was to refine stem detection and develop computer-vision-based methods to better classify water emergence at the xylem. To this end, we collected and manually annotated video data, applying vision- and learning-based methods for detection and classification. Additionally, we explored data augmentation and fine-tuned parameters to identify the most effective models. The identified best-performing models for stem detection and xylem wetness classification were evaluated end-to-end over 20 SWP measurements. Learning-based stem detection via YOLOv8n combined with ResNet50-based classification achieved a Top-1 accuracy of 80.98%, making it the best-performing approach for xylem wetness classification.

We investigate Large Language Models' (LLMs) ability to predict a user's stance on a target given a collection of his/her target-agnostic social media posts (i.e., user-level stance prediction). While we show early evidence that LLMs are capable of this task, we highlight considerable variability in the performance of the model across (i) the type of stance target, (ii) the prediction strategy and (iii) the number of target-agnostic posts supplied. Post-hoc analyses further hint at the usefulness of target-agnostic posts in providing relevant information to LLMs through the presence of both surface-level (e.g., target-relevant keywords) and user-level features (e.g., encoding users' moral values). Overall, our findings suggest that LLMs might offer a viable method for determining public stances towards new topics based on historical and target-agnostic data. At the same time, we also call for further research to better understand LLMs' strong performance on the stance prediction task and how their effectiveness varies across task contexts.

Electrometry based on electromagnetically induced transparency (EIT) in alkali Rydberg vapor cells may suffer reduced sensitivity due to spurious line broadening effects, caused by surface charges, contaminant gases, or other manufacturing defects. In order to draw conclusions about the deleterious effects of potential contaminant gases inside Rydberg electrometry vapor cells, we revisit collisional broadening and shifts of both the D$_2$ line and Rydberg levels of rubidium. Specifically, we measure the broadening and shifts of the $5{\rm S}_{1/2}\rightarrow 5{\rm P}_{3/2}$ (i.e., the D$_2$ line) and $5{\rm S}_{1/2}\rightarrow 5{\rm P}_{3/2}\rightarrow (25{\rm D},27{\rm S},30{\rm D},32{\rm S},35{\rm D},37{\rm S})$ transitions of $^{85}$Rb due to He, Ne, N$_2$ and Ar. By combining these measurements with observations of velocity changing collisions in the sub-Doppler spectrum of the D$_2$ line, we conclude the following: (1) that contaminant gases are most likely not the cause of irregular line shapes or shifts of Rydberg transitions due to the high pressures required, and (2) the sub-Doppler spectrum of the D$_2$ line, through its accompanying loss of contrast at high pressures, can validate that a vapor cell is sufficiently free of contaminant gas for EIT electrometry. We use the theory of Omont, J. Phys. France 38, 1343 (1977), to extend our results to a wide variety of possible contaminant gases and further derive scaling laws applicable to all gases., Comment: 10 pages, 6 figures, 3 tables

Improving the bandwidth of Rydberg atom-based receivers is an ongoing challenge owing to the long-lived Rydberg state lifetimes that limit the refresh rate of ground state atoms. In particular, the LO-based Rydberg mixer approach allows for bandwidths into the few-MHz range. Here, we use heterodyne detection of the Rydberg atom receiver probe laser to separate the negative and positive sidebands that originate from distinct six wave mixing processes, in order to investigate their individual bandwidths. We experimentally confirm the prediction that the negative sideband exhibits a higher bandwidth than the positive sideband. We further explore the effect of coupling and probe laser Rabi frequency on the bandwidth, which we find to be in good agreement with our model. We achieved a maximum experimental (and theoretical) bandwidth of about 11 (11) MHz and 3.5 (5) MHz for the negative and positive sidebands, respectively, from the -3dB roll-off point for optimized field parameters. This work provides insight into the bandwidth-limiting features of Rydberg atom receivers and points the way towards further optimization of their response.

An overview is given of the methods and preliminary results from dedicated beam studies on three topics conducted over five days in July 2023. In the first study, the Fermilab Booster magnets were held constant at magnetic fields corresponding to the injection energy. The beam loss and emittance growth were observed under varying intensity, tunes, and sextupole resonances. The corresponding beam conditions were also simulated with the MADX-SC code~\cite{Schmidt:2644660}. In the second study, measurements of the vertical half-integer resonance and correction methods are conducted for high-intensity beams ramping in the Booster. Finally, syncho-betatron instabilities are observed during transition-crossing in the Booster under strong space-charge conditions., Comment: 30 pages, 26 figures, 36 references, accepted to JINST HB2023 special issue

Voice signals originating from the respiratory tract are utilized as valuable acoustic biomarkers for the diagnosis and assessment of respiratory diseases. Among the employed acoustic features, Mel Frequency Cepstral Coefficients (MFCC) is widely used for automatic analysis, with MFCC extraction commonly relying on default parameters. However, no comprehensive study has systematically investigated the impact of MFCC extraction parameters on respiratory disease diagnosis. In this study, we address this gap by examining the effects of key parameters, namely the number of coefficients, frame length, and hop length between frames, on respiratory condition examination. Our investigation uses four datasets: the Cambridge COVID-19 Sound database, the Coswara dataset, the Saarbrucken Voice Disorders (SVD) database, and a TACTICAS dataset. The Support Vector Machine (SVM) is employed as the classifier, given its widespread adoption and efficacy. Our findings indicate that the accuracy of MFCC decreases as hop length increases, and the optimal number of coefficients is observed to be approximately 30. The performance of MFCC varies with frame length across the datasets: for the COVID-19 datasets (Cambridge COVID-19 Sound database and Coswara dataset), performance declines with longer frame lengths, while for the SVD dataset, performance improves with increasing frame length (from 50 ms to 500 ms). Furthermore, we investigate the optimized combination of these parameters and observe substantial enhancements in accuracy. Compared to the worst combination, the SVM model achieves an accuracy of 81.1%, 80.6%, and 71.7%, with improvements of 19.6%, 16.10%, and 14.90% for the Cambridge COVID-19 Sound database, the Coswara dataset, and the SVD dataset respectively.

The supersolid phase of a dipolar Bose-Einstein condensate has an intriguing excitation spectrum displaying a band structure. Here, the dressing of an impurity in a one-dimensional dipolar supersolid with the excitations of the supersolid is studied. The ground-state energy of the supersolid polaron is calculated using a variational path integral approach, which obtained accurate results for other polaron systems within the Bogoliubov and Fr\"ohlich approximations. A divergence is observed at the superfluid-supersolid phase transition. The polaron radius is also computed, showing that for strong impurity-atom interactions, the polaron can become localized to a single droplet, behaving like a small solid-state polaron., Comment: 8 pages, 5 figures

In this paper, we discuss the various structures associated with maximally monotone and quasidense subsets of the product of a real Banach space and its dual. In the first half of the paper, we give four statements equivalent to the assertion that a maximally monotone subset be quasidense, including the statement that the set be of ``type (NI)''. Then we consider the Fitzpatrick and Gossez extensions of a maximally monotone set to the dual. We give eight equivalent formulations for the Fitzpatrick extension of a quasidense maximally monotone set and prove that in, this case, the Fitzpatrick and Gossez extensions coincide. This leads to the result that a maximally monotone set is quasidense exactly when it is of ``type (D)''. We also give an example of a quasidense maximally monotone set whose Fitzpatrick extension, though maximally monotone, is not quasidense. In the final part of this paper, we prove that a maximally monotone set is quasidense if, and only if, it is of ``type (FP)''. The proof of ``only if'' is much simpler than the two which have been given up to now., Comment: 24 pages

The system of a charged impurity in an interacting Bose gas has gained significant attention due to the long-range ion-atom interactions and the study of transport properties. Here, the ground state energy of a charged Bose polaron is calculated within the Bogoliubov approximation for both the Fr\"ohlich and beyond-Fr\"ohlich Hamiltonians using a generalized Feynman variational path-integral approach, which obtained accurate results for other polaron problems. The generalized approach, which was used to improve the energy result for the neutral polaron, has resulted in a minor improvement, indicating that Feynman's approach is sufficient when the impurity-boson interaction is long-range. Beyond-Fr\"ohlich corrections results in the emergence of a divergence in the polaronic energy indicating a transition between the repulsive and attractive polaron regime. The path-integral approach with the beyond-Fr\"ohlich Hamiltonian is also compared to a field-theory calculation from Christensen et al, 2021. The validity of the Bogoliubov approximation is investigated. The optical absorption has also been calculated within the Bogoliubov approximation for weak ion-atom interactions, and the effect of finite temperature has been studied. We show that the coupling of the ion to an oscillating external electric field offers a straigtforward experimental probe for the charged polaron in a Bose gas, different from but complementary to existing spectroscopic techniques., Comment: 20 pages, 4 figures

In the last decade, computer vision has witnessed the establishment of various training and learning approaches. Techniques like adversarial learning, contrastive learning, diffusion denoising learning, and ordinary reconstruction learning have become standard, representing state-of-the-art methods extensively employed for fully training or pre-training networks across various vision tasks. The exploration of fine-tuning approaches has emerged as a current focal point, addressing the need for efficient model tuning with reduced GPU memory usage and time costs while enhancing overall performance, as exemplified by methodologies like low-rank adaptation (LoRA). Key questions arise: which pre-training technique yields optimal results - adversarial, contrastive, reconstruction, or diffusion denoising? How does the performance of these approaches vary as the complexity of fine-tuning is adjusted? This study aims to elucidate the advantages of pre-training techniques and fine-tuning strategies to enhance the learning process of neural networks in independent identical distribution (IID) cohorts. We underscore the significance of fine-tuning by examining various cases, including full tuning, decoder tuning, top-level tuning, and fine-tuning of linear parameters using LoRA. Systematic summaries of model performance and efficiency are presented, leveraging metrics such as accuracy, time cost, and memory efficiency. To empirically demonstrate our findings, we focus on a multi-task segmentation-classification challenge involving the paracingulate sulcus (PCS) using different 3D Convolutional Neural Network (CNN) architectures by using the TOP-OSLO cohort comprising 596 subjects.

NaNbO3-based antiferroelectric materials offer a promising pathway towards greener and more cost-effective energy storage devices. However, their intrinsic structural instabilities often lead to reduced energy density that compromises their performance and longevity. In this brief communication, we demonstrate how Dark-Field X-ray Microscopy, when carried out on the characteristically weak 1/4{843}pc superstructure reflection, can map the antiferroelectric phase and its strain heterogeneity in typically small, deeply-embedded grains of a NaNbO3 and 0.95NaNbO3-0.05SrSnO3 ceramics, representative of different phase transition behavior. Our results clearly evidences the stabilizing effect of SrSnO3 on the antiferroelectric phase by enhancing the degree of mesostructural order. In doing so, our method establishes a new platform for exploring the impact of disorder on the long-range strain heterogeneity within antiferroelectrics and other materials with modulated crystal structures., Comment: 11 pages, 4 figures

Large language models are increasingly being used to label or rate psychological features in text data. This approach helps address one of the limiting factors of digital trace data - their lack of an inherent target of measurement. However, this approach is also a form of psychological measurement (using observable variables to quantify a hypothetical latent construct). As such, these ratings are subject to the same psychometric considerations of reliability and validity as more standard psychological measures. Here we present a workflow for developing and evaluating large language model based measures of psychological features which incorporate these considerations. We also provide an example, attempting to measure the previously established constructs of attitude certainty, importance and moralization from text. Using a pool of prompts adapted from existing measurement instruments, we find they have good levels of internal consistency but only partially meet validity criteria., Comment: Added example applying the approach to measuring attitude properties from Twitter data

Runaway electrons (REs) are a concern for tokamak fusion reactors from discharge startup to termination. A sudden localized loss of a multi-megaampere RE beam can inflict severe damage to the first wall. Should a disruption occur, the existence of a RE seed may play a significant role in the formation of a RE beam and the magnitude of its current. The application of central electron cyclotron resonance heating (ECRH) in the Tokamak \`a Configuration Variable (TCV) reduces an existing RE seed population by up to three orders of magnitude within only a few hundred milliseconds. Applying ECRH before a disruption can also prevent the formation of a post-disruption RE beam in TCV where it would otherwise be expected. The RE expulsion rate and consequent RE current reduction are found to increase with applied ECRH power. Whereas central ECRH is effective in expelling REs, off-axis ECRH has a comparatively limited effect. A simple 0-D model for the evolution of the RE population is presented that explains the effective ECRH-induced RE expulsion results from the combined effects of increased electron temperature and enhanced RE transport.

Gas-phase metallicity gradients are a crucial element in understanding the chemical evolution of galaxies. We use the FOGGIE simulations to study the metallicity gradients ($\nabla Z$) of six Milky Way-like galaxies throughout their evolution. FOGGIE galaxies generally exhibit steep negative gradients for most of their history, with only a few short-lived instances reaching positive slopes that appear to arise mainly from interactions with other galaxies. FOGGIE concurs with other simulation results but disagrees with the robust observational finding that flat and positive gradients are common at $z>1$. By tracking the metallicity gradient at a rapid cadence of simulation outputs ($\sim 5$--10 Myr), we find that theoretical gradients are highly stochastic: the FOGGIE galaxies spend $\sim 30-50$\% of their time far away from a smoothed trajectory inferred from analytic models or other, less high-cadence simulations. This rapid variation makes instantaneous gradients from observations more difficult to interpret in terms of physical processes. Because of these geometric and stochastic complications, we explore non-parametric methods of quantifying the evolving metallicity distribution at $z > 1$. We investigate how efficiently non-parametric measures of the 2-D metallicity distribution respond to metal production and mixing. Our results suggest that new methods of quantifying and interpreting gas-phase metallicity will be needed to relate trends in upcoming high-$z$ {\it JWST} observations with the underlying physics of gas accretion, expulsion, and recycling in early galaxies., Comment: Submitted to ApJ

Optimizing grain boundary characteristics in polycrystalline materials can improve their properties. Many processing methods have been developed for grain boundary manipulation, including the use of intense radiation in certain applications. In this work, we used X-ray free electron laser pulses to irradiate single-crystalline bismuth selenide (Bi2Se3) and observed grain boundary formation and subsequent grain rotation in response to the X-ray radiation. Our observations with simultaneous transmission X-ray microscopy and X-ray diffraction demonstrate how intense X- ray radiation can rapidly change size and texture of grains., Comment: 37 pages, 11 figures including 6 supplemental figures

We show that the use of an optical frequency comb probe leads to dramatically improved bandwidth (as high as 12+/-1 MHz) for the detection of modulated radio frequencies in Rydberg atom-based electrometry.

Rydberg atom-based electric field sensing can provide all-optical readout of radio frequency fields in a dielectric environment. However, because a single set of optical fields is typically used to prepare the Rydberg state and read out its response to RF fields, it is challenging to perform simultaneous and independent measurements of the RF field(s). Here we show that using two independent schemes to prepare and read out the same Rydberg state can be used to perform independent measurements in general, which we demonstrate specifically by resolving the the RF polarization. We expect this work will be useful for fiber-coupled sensor heads where spatial multiplexing is challenging, as well as for complex multi-level sensing schemes.

COVID-19 has affected more than 223 countries worldwide and in the Post-COVID Era, there is a pressing need for non-invasive, low-cost, and highly scalable solutions to detect COVID-19. We develop a deep learning model to identify COVID-19 from voice recording data. The novelty of this work is in the development of deep learning models for COVID-19 identification from only voice recordings. We use the Cambridge COVID-19 Sound database which contains 893 speech samples, crowd-sourced from 4352 participants via a COVID-19 Sounds app. Voice features including Mel-spectrograms and Mel-frequency cepstral coefficients (MFCC) and CNN Encoder features are extracted. Based on the voice data, we develop deep learning classification models to detect COVID-19 cases. These models include Long Short-Term Memory (LSTM) and Convolutional Neural Network (CNN) and Hidden-Unit BERT (HuBERT). We compare their predictive power to baseline machine learning models. HuBERT achieves the highest accuracy of 86\% and the highest AUC of 0.93. The results achieved with the proposed models suggest promising results in COVID-19 diagnosis from voice recordings when compared to the results obtained from the state-of-the-art., Comment: arXiv admin note: text overlap with arXiv:2209.03727

The Large Magellanic Cloud (LMC) is home to many HII regions, which may lead to significant outflows. We examine the LMC's multiphase gas ($T\sim10^{4-5}$ K) in HI, SII, SiIV, and CIV using 110 stellar sight lines from the HST's Ultraviolet Legacy Library of Young Stars as Essential Standards (ULLYSES) program. We develop a continuum fitting algorithm based on the concept of Gaussian Process regression and identify reliable LMC interstellar absorption over $v_{\rm helio}=175-375$ km s$^{-1}$. Our analyses show disk-wide ionized outflows in SiIV and CIV across the LMC with bulk velocities of $|v_{\rm out, bulk}|\sim20-60$ km s$^{-1}$, which indicates that most of the outflowing mass is gravitationally bound. The outflows' column densities correlate with the LMC's star formation rate surface densities ($\Sigma_{\rm SFR}$), and the outflows with higher $\Sigma_{\rm SFR}$ tend to be more ionized. Considering outflows from both sides of the LMC as traced by CIV, we conservatively estimate a total outflow rate of $\dot{M}_{\rm out}\gtrsim 0.03~M_\odot {\rm yr}^{-1}$ and a mass loading factor of $\eta\gtrsim 0.15$. We compare the LMC's outflows with those detected in starburst galaxies and simulation predictions, and find a universal scaling relation of $|v_{\rm out, bulk}|\propto \Sigma_{\rm SFR}^{0.23}$ over a wide range of star-forming conditions ($\Sigma_{\rm SFR}\sim10^{-4.5}-10^{2}~M_\odot {\rm yr}^{-1} {\rm kpc}^{-2}$). Lastly, we find that the outflows are co-rotating with the LMC's young stellar disk and the velocity field does not seem to be significantly impacted by external forces; we thus speculate on the existence of a bow shock leading the LMC, which may have shielded the outflows from ram pressure as the LMC orbits the Milky Way., Comment: Accepted for publication in ApJ. Key findings can be found in Figures 9-12. Main updates from the previous version include new estimates on star formation rate surface densities. Normalized SII, SiIV, and CIV line spectra derived for this work are published as a High Level Science Product called LMC-FLOWS (doi: 10.17909/hz0m-np43), available on website: https://archive.stsci.edu/hlsp/lmc-flows

We present a three-photon based fluorescence readout method where the strength of the fluorescence scales with the strength of the radio-frequency (RF) field being applied. We compare this method to conventional three-photon electromagnetically-induced transparency (EIT) and electromagnetically-induced absorption (EIA). Our demonstrated EIA/EIT sensitivity in the collinear three-photon Cesium system is the best reported to date at roughly 30 uVm^{-1}Hz^{-1/2}. The fluorescence is nearly 4 fold better in sensitivity compared to EIA/EIT readout., Comment: 9 figure, quantum optics, rydberg electrometry

We explore the relationships between the [O/H] gas-phase metallicity radial gradients and multiple galaxy properties for 238 star-forming galaxies at 0.6