Miracle-dz/UniFAR-FTUs huggingface dataset:
Chemical abundances and radial velocities in the extremely metal-poor galaxy DDO 68

We present chemical abundances and radial velocities of six HII regions in the extremely metal-poor star-forming dwarf galaxy DDO 68. They are derived from deep spectra in the wavelength range 3500 - 10,000 {\AA}, acquired with the Multi Object Double Spectrograph (MODS) at the Large Binocular Telescope (LBT). In the three regions where the [O III]$\lambda$4363 {\AA} line was detected, we inferred the abundance of He, N, O, Ne, Ar, and S through the "direct" method. We also derived the oxygen abundances of all the six regions adopting indirect method calibrations. We confirm that DDO 68 is an extremely metal-poor galaxy, and a strong outlier in the luminosity - metallicity relation defined by star-forming galaxies. With the direct-method we find indeed an oxygen abundance of 12+log(O/H)=7.14$\pm$0.07 in the northernmost region of the galaxy and, although with large uncertainties, an even lower 12+log(O/H)=6.96$\pm$0.09 in the "tail". This is, at face value, the most metal-poor direct abundance detection of any galaxy known. We derive a radial oxygen gradient of -0.06$\pm$0.03 dex/kpc (or -0.30 dex $R_{25}^{-1}$) with the direct method, and a steeper gradient of -0.12$\pm$0.03 dex/kpc (or -0.59 dex $R_{25}^{-1}$) from the indirect method. For the $\alpha$-element to oxygen ratios we obtain values in agreement with those found in other metal-poor star-forming dwarfs. For nitrogen, instead, we infer much higher values, leading to log(N/O)$\sim-1.4$, at variance with the suggested existence of a tight plateau at $-1.6$ in extremely metal poor dwarfs. The derived helium mass fraction ranges from Y=0.240$\pm$0.005 to Y=0.25$\pm$0.02, compatible with standard big bang nucleosynthesis. Finally, we measured HII region radial velocities in the range 479$-$522 km/s from the tail to the head of the "comet", consistent with the rotation derived in the HI.
CAMBRIDGE WORKING PAPERS IN ECONOMICS JANEWAY INSTITUTE WORKING PAPERS Quantifying excess mortality among non COVID-19 patients in healthcare settings

COVID-19 drastically increased demand- and supply pressures faced by healthcare systems. Increased pressures may have negative spillovers into non COVID-19 care which can cause preventable excess deaths among patients seeking medical help for reasons unrelated to COVID-19. This paper finds substantial and robust evidence of such non COVID-19 excess deaths among hospital patients leveraging data from an integrated public healthcare system: the NHS in England. We find that there is at least one additional preventable death among hospital patients seeking medical help for reasons unrelated to COVID-19 for every 30 deaths that can be linked to COVID-19. In aggregate, there were 4,003 such excess deaths during the first twelve months of the pandemic. At the healthcare provider level, the increase in non COVID-19 excess deaths is sharply increasing in COVID-19 induced pressures on hospitals. COVID-19 drastically increased demand- and supply pressures faced by healthcare systems. Increased pressures may have negative spillovers into non COVID-19 care which can cause preventable excess deaths among patients seeking medical help for reasons unrelated to COVID-19. This paper ﬁnds substantial and robust evidence of such non COVID-19 excess deaths among hospital patients leveraging data from an integrated public healthcare system: the NHS in England. We ﬁnd that there is at least one additional preventable death among hospital patients seeking medical help for reasons unrelated to COVID-19 for every 30 deaths that can be linked to COVID-19. In aggregate, there were 4,003 such excess deaths during the ﬁrst twelve months of the pandemic. At the healthcare provider level, the increase in non COVID-19 excess deaths is sharply increasing in COVID-19 induced pressures on hospitals.
Psychological Understanding of Textual journals using Natural Language Processing approaches

Recent NLP advancements have improved the state-of-the-art in well-known datasets and are appealing more attention day by day. However, as the models become more complicated, the ability to provide interpretable and understandable results is becoming harder so the tradeoff between accuracy and interpretability is a concern that is yet to be addressed. In this project, the aim is to utilize state-of-the-art NLP models to provide meaningful insight from psychological real-world documents that contain complex structures. The project involves two main chapters each including a different dataset. The first chapter is related to binary classification on a personality detection dataset, while the second one is about sentiment analysis and Topic Modeling of sleep-related reports.
Examining Relationships that Matter: A Qualitative Study of Black Women in Doctoral Education

The purpose of this study was to explore how and why various relationships bolstered the success of Black women doctoral students by contributing to their motivation and persistence in graduate education. Using the voices of 14 Black women doctoral students within the United States and community cultural wealth as a theoretical lens, this qualitative study sought to examine the nature and importance of supportive relationships that existed during their graduate studies. Findings from this study revealed that family served as a motivator for enrollment and degree completion, a sounding board during trying times, and a space for processing the doctoral experience. Friends and professional associations transmitted various forms of social capital, and mentors served as advocates and facilitators of professional socialization. Additionally, social media played a significant role in helping Black women establish networks when there was limited visibility of or access to other Black women in their graduate programs. From this study, academic programs may be able to glean which aspects of these different relationship types (e.g., family, friends, mentors) matter and develop mechanisms for incorporating them into the experiences of Black women (and other minoritized groups) in doctoral programs.
Sentence-Incremental Neural Coreference Resolution

We propose a sentence-incremental neural coreference resolution system which incrementally builds clusters after marking mention boundaries in a shift-reduce method. The system is aimed at bridging two recent approaches at coreference resolution: (1) state-of-the-art non-incremental models that incur quadratic complexity in document length with high computational cost, and (2) memory network-based models which operate incrementally but do not generalize beyond pronouns. For comparison, we simulate an incremental setting by constraining non-incremental systems to form partial coreference chains before observing new sentences. In this setting, our system outperforms comparable state-of-the-art methods by 2 F1 on OntoNotes and 6.8 F1 on the CODI-CRAC 2021 corpus. In a conventional coreference setup, our system achieves 76.3 F1 on OntoNotes and 45.5 F1 on CODI-CRAC 2021, which is comparable to state-of-the-art baselines. We also analyze variations of our system and show that the degree of incrementality in the encoder has a surprisingly large effect on the resulting performance.
Simultaneous precision spectroscopy of 
pp
, 
Be7
, and 
pep
 solar neutrinos with Borexino Phase-II

We present the first simultaneous measurement of the interaction rates of $pp$, $^7$Be, and $pep$ solar neutrinos performed with a global fit to the Borexino data in an extended energy range (0.19-2.93)$\,$MeV. This result was obtained by analyzing 1291.51$\,$days of Borexino Phase-II data, collected between December 2011 and May 2016 after an extensive scintillator purification campaign. We find: rate($pp$)$\,$=$\,$$134$$\,$$\pm$$\,$$10$$\,$($stat$)$\,$$^{\rm +6}_{\rm -10}$$\,$($sys$)$\,$cpd/100$\,$t, rate($^7$Be)$\,$=$\,$$48.3$$\,$$\pm$$\,$$1.1$$\,$($stat$)$\,$$^{\rm +0.4}_{\rm -0.7}$$\,$($sys$)$\,$cpd/100$\,$t, and rate($pep$)$\,$=$\,$$2.43$$\pm$$\,$$0.36$$\,$($stat$)$^{+0.15}_{-0.22}$$\,$($sys$)$\,$cpd/100$\,$t. These numbers are in agreement with and improve the precision of our previous measurements. In particular, the interaction rate of $^7$Be $\nu$'s is measured with an unprecedented precision of 2.7%, showing that discriminating between the high and low metallicity solar models is now largely dominated by theoretical uncertainties. The absence of $pep$ neutrinos is rejected for the first time at more than 5$\,$$\sigma$. An upper limit of $8.1$$\,$cpd/100$\,$t (95%$\,$C.L.) on the CNO neutrino rate is obtained by setting an additional constraint on the ratio between the $pp$ and $pep$ neutrino rates in the fit. This limit has the same significance as that obtained by the Borexino Phase-I (currently providing the tightest bound on this component), but is obtained by applying a less stringent constraint on the $pep$ $\nu$ flux.
Inflation in times of overlapping emergencies: Systemically significant prices from an input-output perspective

In the overlapping global emergencies of the pandemic, climate change and geopolitical confrontations, supply shocks have become frequent and inflation has returned. This raises the question how sector-specific shocks are related to overall price stability. This paper simulates price shocks in an input-output model to identify sectors which present systemic vulnerabilities for monetary stability in the US. We call these prices systemically significant. We find that in our simulations the pre-pandemic average price volatilities and the price shocks in the COVID-19 and Ukraine war inflation yield an almost identical set of systemically significant prices. The sectors with systemically significant prices fall into three groups: energy, basic production inputs other than energy, basic necessities, and commercial and financial infrastructure. Specifically, they are “Petroleum and coal products”, “Oil and gas extraction”, “Utilities”, “Chemical products”, “Farms”, “Food and beverage and tobacco products”, “Housing”, and “Wholesale trade”. We argue that in times of overlapping emergencies, economic stabilization needs to go beyond monetary policy and requires institutions and policies that can target these systemically significant sectors. JEL Codes: C67, E31, E61
Spacetime Instability and the Problems with Low Energy Quantum Gravity

In this paper we discuss spacetime instability problems in effective field theories of the quantum gravity (QG). The effective action of the gravity requires higher-derivative curvature terms $R^{2}, { R }_{ \mu \nu }{ R }^{ \mu \nu }, R_{\mu\nu\kappa\lambda} R^{\mu\nu\kappa\lambda}\dots$ and they are leading quantum gravitational corrections. Although these higher-curvature terms are indispensable for the construction of the semiclassical or quantum gravity, they lead to several pathologies. We clearly show that even if they are Planck-suppressed operators they lead to serious consequences of the spacetime stability and, de Sitter or radiation dominated Universe are highly unstable for the Hubble perturbation. Furthermore, these curvature terms also violate the null energy condition (NEC) which is required for the self-consistent theories or system. The standard effective field theory of the gravity might fail to describe the observed Universe.
Contract Enforcement and Decentralized Consensus: The Case of Slashing∗

Many new blockchain applications rely on the “stake-and-slash” mechanism to align incentives. We point out that the design of such “contracting” problems cannot be detached from the details of the decentralized consensus formation process. To illustrate our theoretical argument, we empirically investigate Ethereum’s beacon chain – an upgrade to a proof-of-stake system. Based on data from Beaconcha.in, the leading Ethereum beacon chain explorer, we find that more than 75% of Byzantine actions have dodged penalty (slashing). Ongoing research is further investigating whether the finding reflects flaws in Ethereum’s incentive design or bugs from a major blockchain explorer.
Job Market Paper How Do Firms Respond to Gender Quotas? Evidence From California’s Senate Bill 826

More than one-third of US-listed companies had all-male corporate boards in 2015. Quotas are discussed as policy levers to increase gender diversity, but there is much controversy whether they can increase female representation without harming organizational outcomes. Using the passage of a California law in 2018 that required the presence of at least one woman on corporate boards by the end of the following year, I estimate the effects of gender quotas on firm performance. I find the quota reduced the share of all-male boards by thirty percentage points within one year, with no reductions in operating performance, firm values, or shareholder returns within three years. These results question why all-male boards were prevalent prior to the legislation. I find that women directors are less likely to possess top-level experience and employment connections with corporate executives, which both appear as viable explanations. These findings provide insight on why women continue to lack representation in corporate leadership. *I thank Michael Best, Sandra Black, Bentley MacLeod, Justin McCrary, and Suresh Naidu for guidance. I thank seminar participants at Columbia University, University of East Anglia, and Washington University at St. Louis for helpful suggestions. Yvon Lu, Jackson McBride, Michael Duarte, Stanley Jian, Nicole Lindley, Sarah Wang, Annaliese Wee, Hanlin Zhang, Rebekah Neuman, and Isaac Bennett provided capable research assistance. I acknowledge funding from Columbia’s Program for Economic Research. †Department of Economics, Columbia University. Email: b.gopal@columbia.edu
Gravitational Lensing & Stellar Dynamics: Dark-Matter and Baryons in Early-type Galaxies to z=1

Gravitational lensing and stellar dynamics provide two complementary, nearly orthogonal, constraints on the mass distribution of early-type lens galaxies. This allows the luminous and dark-matter distribution in higher-redshift (z>0.1) galaxies to be studied beyond the limitations of each individual method. Two surveys have been initiated to compile a large sample of early-type galaxies suitable to lensing and dynamical studies: (1) The Lenses Structure & Dynamics (LSD) Survey and (2) the Sloan Lens ACS (SLACS) Survey. Using spherically symmetric mass models, I illustrated how lensing and dynamical constraints can be used to measure the ``effective'' density slope (gamma') of galaxies inside their Einstein radii and estimate the typical error on this determination. The main results from the LSD survey thus far are: (i) Massive (typically >L_*) early-type galaxies at z=0.5-1 contain a significant fraction f_CDM=0.4-0.7 of dark matter inside their Einstein radii. [The null-hypothesis, f_CDM=0, is excluded at the >99% in all analyzed systems. ] (ii) The inner CDM density slope is gamma_CDM=1.3^{+0.2}_{-0.3} (68% CL). (iii) The total density slope gamma' = 1.9 +- 0.1 (with 0.3 rms scatter in the sample). The intrinsic scatter of 15% in gamma' is consistent with local dynamical studies and can lead to a 30% rms scatter in inferred values of H_0 from lens time-delays, when purely isothermal mass models are assumed. Hence, the common practice to assume that lens galaxies are perfectly isothermal should be abandoned, especially in cases where this assumption is critical.
Parkinson’s disease impairs cortical sensori-motor decision-making cascades

The transformation from perception to action requires a set of decisions about the nature of the percept, identification and selection of response options, and execution of the appropriate motor response. The unfolding of such decisions is mediated by distributed representations of the decision variables - evidence and intentions - that are represented through oscillatory activity across the cortex. Here we combine magneto-electroencephalography and linear ballistic accumulator models of decision-making to reveal the impact of Parkinson's disease during the selection and execution of action. We used a visuomotor task in which we independently manipulated uncertainty in sensory and action domains. A generative accumulator model was optimized to single-trial neurophysiological correlates of human behaviour, mapping the cortical oscillatory signatures of decision-making, and relating these to separate processes accumulating sensory evidence and selecting a motor action. We confirmed the role of widespread beta oscillatory activity in shaping the feed-forward cascade of evidence accumulation from resolution of sensory inputs to selection of appropriate responses. By contrasting the spatiotemporal dynamics of evidence accumulation in age-matched healthy controls and people with Parkinson's disease, we identified disruption of the beta-mediated cascade of evidence accumulation as the hallmark of atypical decision-making in Parkinson's disease. In frontal cortical regions, there was inefficient processing and transfer of perceptual information. Our findings emphasize the intimate connection between abnormal visuomotor function and pathological oscillatory activity in neurodegenerative disease. We propose that disruption of the oscillatory mechanisms governing fast and precise information exchanges between the sensory and motor systems contributes to behavioural changes in people with Parkinson's disease.
DUST IN THE CORES OF EARLY-TYPE GALAXIES

The dust properties of all early-type galaxies imaged with the Planetary Camera of the Hubble Space Telescope in cycles I-III are examined. Dust is detected in 31 out of 64 galaxies, although the sample is biased against the detection of dust. From the distribution of observed axis ratios of the dust features it is inferred that 78%+/-16% of early-type galaxies contain nuclear dust. The detection rate in radio galaxies is higher (72%+/-16%) than in radio-quiet galaxies (33%+/-9%). In radio galaxies with double radio structure, the dust is usually found perpendicular to the radio axis. Dust masses range from 10(3)-10(7) solar masses. From the dependence of the misalignment angle (the angle between dust major axis and galaxy major axis) on size and appearance of the dust, it is found that dust features with semimajor-axis size a(d)>250 pc are generally not settled. If it is assumed that dust lanes with a(d)
First Millimeter Flares Detected from ϵ Eridani with the Atacama Large Millimeter/submillimeter Array

We report the detection of three large millimeter flaring events from the nearby Sun-like, ϵ Eridani, found in archival Atacama Large Millimeter/submillimeter Array (ALMA) 12 m and Atacama Compact Array observations at 1.33 mm taken from 2015 January 17 to 18 and 2016 October 24 to November 23, respectively. This is the first time that flares have been detected from a Sun-like star at millimeter wavelengths. The largest flare among our data was detected in the ALMA observations on 2015 January 17 from 20:09:10.4–21:02:49.3 UT with a peak flux density of 28 ± 7 mJy and a duration of 9 s. The peak brightness of the largest flare is 3.4 ± 0.9 × 1014 erg s−1 Hz−1, a factor of >50× times brighter than the star’s quiescent luminosity and >10× brighter than solar flares observed at comparable wavelengths. We find changes in the spectral index (F ν ∝ ν α ) at the flare peak, with α = 1.81 ± 1.94 and a lower limit on the fractional linear polarization ∣Q/I∣ = 0.08 ± 0.12. This positive spectral index is more similar to millimeter solar flares, differing from M-dwarf flares also detected at millimeter wavelengths that exhibit steeply negative spectral indices.
Investigating the [C ii]-to-H i Conversion Factor and the H i Gas Budget of Galaxies at z ≈ 6 with Hydrodynamic Simulations

One of the most fundamental baryonic matter components of galaxies is the neutral atomic hydrogen (H i). At low redshifts, this component can be traced directly through the 21 cm transition, but to infer the H i gas content of the most distant galaxies, a viable tracer is needed. We here investigate the fidelity of the fine-structure transition of the (2 P 3/2 − 2 P 1/3) transition of singly ionized carbon C ii at 158 μm as a proxy for H i in a set simulated galaxies at z ≈ 6, following the work by Heintz et al. We select 11,125 star-forming galaxies from the simba simulations, with far-infrared line emissions postprocessed and modeled within the Sigame framework. We find a strong connection between C ii and H i, with the relation between this C ii-to-H i relation (β [C II]) being anticorrelated with the gas-phase metallicity of the simulated galaxies. We further use these simulations to make predictions for the total baryonic matter content of galaxies at z ≈ 6, and specifically the H i gas mass fraction. We find mean values of M H I/M ⋆ = 1.4 and M H I/M bar,tot = 0.45. These results provide strong evidence for H i being the dominant baryonic matter component by mass in galaxies at z ≈ 6.
Spinning strings in AdS5 × S5: one-loop correction to energy in SL(2) sector

We consider a circular string with spin S in AdS5 wrapped around big circle of S5 and carrying also momentum J. The corresponding N = 4 SYM operator belongs to the SL(2) sector, i.e. has tr(DSZJ)+. structure. The leading large J term in its 1-loop anomalous dimension can be computed using Bethe ansatz for the SL(2) spin chain and was previously found to match the leading term in the classical string energy. The string solution is stable at large J, and the Lagrangian for string fluctuations has constant coefficients, so that the 1-loop string correction to the energy E1 is given simply by the sum of characteristic frequencies. Curiously, we find that the leading term in the zero-mode part of E1 is the same as a 1/J correction to the one-loop anomalous dimension on the gauge theory (spin chain) side that was found in [1]. However, the contribution of non-zero string modes does not vanish. We also discuss the ``fast string'' expansion of the classical string action which coincides with the coherent state action of the SL(2) spin chain at the first order in λ, and extend this expansion to higher orders clarifying the role of the S5 winding number.
Masked Autoencoders are Articulatory Learners

Articulatory recordings track the positions and motion of different articulators along the vocal tract and are widely used to study speech production and to develop speech technologies such as articulatory based speech synthesizers and speech inversion systems. The University of Wisconsin X-Ray Mi-crobeam (XRMB) dataset is one of various datasets that provide articulatory recordings synced with audio recordings. The XRMB articulatory recordings employ pellets placed on a number of articulators which can be tracked by the mi-crobeam. However, a significant portion of the articulatory recordings are mistracked, and have been so far unusable. In this work, we present a deep learning based approach using Masked Autoencoders to accurately reconstruct the mistracked articulatory recordings for 41 out of 47 speakers of the XRMB dataset. Our model is able to reconstruct articulatory trajectories that closely match ground truth, even when three out of eight articulators are mistracked, and retrieve 3.28 out of 3.4 hours of previously unusable recordings.