Miracle-dz/UniFAR-FTUs huggingface dataset:
13 Lesbian and Bisexual Women's Physical Health

R esearchers have documented alarming health disparities between people of color and white individuals in the United States (Adler & Rehkopf, 2008), but only recently have they begun to examine potential disparities based on sexual orientation-especially for sexual minority women. The U.S. Department of Health and Human Services (HHS, 2010) characterized health disparities as differences in health impacting groups of people who have systematically encountered obstacles to healthcare as a result of social, economic, and environmental disadvantage. In fact, the U.S. Centers for Disease Control and Prevention (CDC) (2011) identified health disparities related to sexual orientation as one of the main gaps in current health disparities research. This research is important in determining whether sexual minority women as a group are at risk for adverse health outcomes and, if so, what preventive measures or other interventions are needed to address the disparities. To date, we know little about the health needs of sexual minority women, hindering the development of relevant public policies and programs (Krehely, 2009). The limited data on the health of lesbians, gay men, bisexuals, and transgender individuals were evident in Boehmer's ( 2002) analysis of 3.8 million citations of articles published between 1980 and 1999. She found only 3800 ( 0.1%) related to lesbian, gay, bisexual, and transgender issuesi a recent review is consistent (Snyder, 2011). The dearth of relevant data on sexual minority women specifically led the U.S. Institute of Medicine in 1991 to commission a report on lesbian health, highlighting the need for population-based research on the prevalence and incidence of clinical problems in lesbians (Solarz, 1999), and again in 2010 to commission a report on lesbian, gay, bisexual, and transgender health (Institute of Medicine, 2011). To date, most of the research on health disparities among sexual minorities has focused not on physical health but on mental health outcomes, including alcohol and substance use (e.g., Cochran, Sullivan, & Mays, 2003)i see Cochran and Mays, Chapter 15, this volume. Fewer studies have focused specifically on physical health outcomes among lesbian and bisexual women, whose situations and concerns appear to be largely different from those of gay men (Conron, Mimiaga, & Landers, 2010). In this chapter, we consider the challenges of conducting research to examine health disparities based on sexual orientation, particularly for sexual minority women, and describe some of the major studies in this area. We briefly review the evidence for disparities in cardiovascular disease and cancer as well as sexually transmitted infections, asthma, and diabetes. Disparities in risk factors (e.g., obesity, smoking) for adverse health outcomes are also presented. We consider the factors and mechanisms that might place sexual minority women at greater risk for compromised health and conclude with directions for future research.
Impact of iron fertilisation on atmospheric CO2 during the last glaciation

Abstract. While several processes have been identified to explain the decrease in atmospheric CO2 during glaciations, a better quantification of the contribution of each of these processes is needed. For example, enhanced aeolian iron input into the ocean during glacial times has been suggested to drive a 5 to 28 ppm atmospheric CO2 decrease. Here, we constrain this contribution by performing a set of sensitivity experiments with different aeolian iron input patterns and iron solubility factors under boundary conditions corresponding to 70 000 years before present (70 ka), a time period characterised by the first observed peak in glacial dust flux. We show that the decrease in CO2 as a function of Southern Ocean iron input follows an exponential decay relationship. This exponential decay response arises due to the saturation of the biological pump efficiency and levels out at ∼21 ppm in our simulations. We show that the changes in atmospheric CO2 are more sensitive to the solubility of iron in the ocean than the regional distribution of the iron fluxes. If surface water iron solubility is considered constant through time, we find a CO2 drawdown of ∼4 to ∼8 ppm. However, there is evidence that iron solubility was higher during glacial times. A best estimate of solubility changing from 1 % during interglacials to 3 % to 5 % under glacial conditions yields a ∼9 to 11 ppm CO2 decrease at 70 ka, while a plausible range of CO2 drawdown between 4 to 16 ppm is obtained using the wider but possible range of 1 % to 10 %. This would account for ∼12 %–50 % of the reconstructed decrease in atmospheric CO2 (∼32 ppm) between 71 and 64 ka. We further find that in our simulations the decrease in atmospheric CO2 concentration is solely driven by iron fluxes south of the Antarctic polar front, while iron fertilisation elsewhere plays a negligible role.
Hard X-ray view on intermediate polars in theGaiaera

The hardness of the X-ray spectra of intermediate polars (IPs) is determined mainly by the white dwarf (WD) compactness (mass-radius ratio, M/R) and, thus, hard X-ray spectra can be used to constrain the WD mass. An accurate mass estimate requires the finite size of the WD magnetosphere R_m to be taken into the account. We suggested to derive it either directly from the observed break frequency in power spectrum of X-ray or optical lightcurves of a polar, or assuming the corotation. Here we apply this method to all IPs observed by NuSTAR (10 objects) and Swift/BAT (35 objects). For the dwarf nova GK Per we also observe a change of the break frequency with flux, which allows to constrain the dependence of the magnetosphere radius on the mass-accretion rate. For our analysis we calculated an additional grid of two-parameter (M and R_m/R) model spectra assuming a fixed, tall height of the accretion column H_sh/R=0.25, which is appropriate to determine WD masses in low mass-accretion IPs like EX\,Hya. Using the Gaia Data Release 2 we obtain for the first time reliable estimates of the mass-accretion rate and the magnetic field strength at the WD surface for a large fraction of objects in our sample. We find that most IPs accrete at rate of ~10^{-9} M_Sun/yr, and have magnetic fields in the range 1--10 MG. The resulting WD mass average of our sample is 0.79 +/- 0.16 M_Sun, which is consistent with earlier estimates.
Modelling the chemistry of star-forming filaments – II. Testing filament characteristics with synthetic observations

We present synthetic continuum and $^{13}$CO and C$^{18}$O line emission observations of dense and cold filaments. The filaments are dynamically evolved using 3D-MHD simulations that include one of the largest on-the-fly chemical networks used to date, which models the detailed evolution of H$_2$ and CO. We investigate the reliability of observable properties, in particular filament mass and width, under different simulation conditions like magnetic field orientation and cosmic ray ionisation rate. We find that filament widths of $\sim$0.1 pc can be probed with both line and continuum emission observations with a high accuracy (deviations $\leq$ 20%). However, the width of more narrow filaments can be significantly overestimated by up to a factor of a few. Masses obtained via the dust emission are accurate within a few percent whereas the masses inferred from molecular line emission observations deviate from the actual mass by up to a factor of 10 and show large differences for different $J$ transitions. The inaccurate estimate of filament masses and widths of narrow filaments using molecular line observations can be attributed to (i) the non-isothermal state of the filaments, (ii) optical depth effects, and (iii) the subthermally excited state of CO, while inclination effects and opacity correction only influence the obtained masses and widths by less than 50%. Both, mass and width estimates, can be improved by using two isotopes to correct for the optical depth. Since gas and dust temperature generally differ (by up to 25 K), the filaments appear more gravitationally unstable if the (too low) dust temperature is used for the stability analysis.
Global Ozone Monitoring Experiment-2 (GOME-2) daily and monthly level-3 products of atmospheric trace gas columns

Abstract. We introduce the new Global Ozone Monitoring Experiment-2 (GOME-2) daily and monthly level-3 product of total column ozone (O3), total and tropospheric column nitrogen dioxide (NO2), total column water vapour, total column bromine oxide (BrO), total column formaldehyde (HCHO), and total column sulfur dioxide (SO2) (daily products https://doi.org/10.15770/EUM_SAF_AC_0048, AC SAF, 2023a; monthly products https://doi.org/10.15770/EUM_SAF_AC_0049, AC SAF, 2023b). The GOME-2 level-3 products aim to provide easily translatable and user-friendly data sets to the scientific community for scientific progress as well as to satisfy public interest. The purpose of this paper is to present the theoretical basis as well as the verification and validation of the GOME-2 daily and monthly level-3 products. The GOME-2 level-3 products are produced using the overlapping area-weighting method. Details of the gridding algorithm are presented. The spatial resolution of the GOME-2 level-3 products is selected based on the sensitivity study. The consistency of the resulting level-3 products among three GOME-2 sensors is investigated through time series of global averages, zonal averages, and bias. The accuracy of the products is validated by comparison to ground-based observations. The verification and validation results show that the GOME-2 level-3 products are consistent with the level-2 data. Small discrepancies are found among three GOME-2 sensors, which are mainly caused by the differences in the instrument characteristic and level-2 processor. The comparison of GOME-2 level-3 products to ground-based observations in general shows very good agreement, indicating that the products are consistent and fulfil the requirements to serve the scientific community and general public.
Real-Time Caustics Using Cascaded Image-Space Photon Tracing

Caustics are formed when transparent or specular materials focus many light rays onto confined areas. Such effects are among the most challenging optical effects to render. Typical path tracing algorithms need many light ray samples to form realistic caustic highlights and/or clever strategies to sample the most relevant light paths. This paper presents an approach for rendering caustics from one specular bounce at an interactive performance by using cascaded image-space photon tracing based on both G-buffer (camera perspective) and Reflective Shadow Maps (light source perspective). A denoiser is applied to remove Monte Carlo noise before applying the caustics texture. Our results demonstrate caustics with more realistic and precise details compared to state-of-the-art Caustics Mapping, at real-time frame rates even on moderately powerful GPUs.
ACORN: Input Validation for Secure Aggregation

Secure aggregation enables a server to learn the sum of client-held vectors in a privacy-preserving way, and has been suc-cessfully applied to distributed statistical analysis and machine learning. In this paper, we both introduce a more efﬁcient secure aggregation construction and extend secure aggregation by enabling input validation , in which the server can check that clients’ inputs satisfy required constraints such as L 0 , L 2 , and L ∞ bounds. This prevents malicious clients from gaining disproportionate inﬂuence on the computed aggregated statistics or machine learning model. Our new secure aggregation protocol improves the computational efﬁciency of the state-of-the-art protocol of Bell et al. (CCS 2020) both asymptotically and concretely: we show via experimental evaluation that it results in 2-8X speedups in client computation in practical scenarios. Likewise, our extended protocol with input validation improves on prior work by more than 30X in terms of client communication (with comparable computation costs). Compared to the base protocols without input validation, the extended protocols incur only 0 . 1X additional communication, and can process binary indicator vectors of length 1M, or 16-bit dense vectors of length 250K, in under 80s of computation per client.
STUNT: Few-shot Tabular Learning with Self-generated Tasks from Unlabeled Tables

Learning with few labeled tabular samples is often an essential requirement for industrial machine learning applications as varieties of tabular data suffer from high annotation costs or have difficulties in collecting new samples for novel tasks. Despite the utter importance, such a problem is quite under-explored in the field of tabular learning, and existing few-shot learning schemes from other domains are not straightforward to apply, mainly due to the heterogeneous characteristics of tabular data. In this paper, we propose a simple yet effective framework for few-shot semi-supervised tabular learning, coined Self-generated Tasks from UNlabeled Tables (STUNT). Our key idea is to self-generate diverse few-shot tasks by treating randomly chosen columns as a target label. We then employ a meta-learning scheme to learn generalizable knowledge with the constructed tasks. Moreover, we introduce an unsupervised validation scheme for hyperparameter search (and early stopping) by generating a pseudo-validation set using STUNT from unlabeled data. Our experimental results demonstrate that our simple framework brings significant performance gain under various tabular few-shot learning benchmarks, compared to prior semi- and self-supervised baselines. Code is available at https://github.com/jaehyun513/STUNT.
The impact of galaxy formation on satellite kinematics and redshift-space distortions

Galaxy surveys aim to map the large-scale structure of the Universe and use redshift space distortions to constrain deviations from general relativity and to probe the existence of mas- sive neutrinos. However, the amount of information that can be extracted will be limited by the accuracy of theoretical models used to analyze the data. Here, by using the L-Galaxies semi-analytical model run over the MXXL N-body simulation, we assess the impact of galaxy formation on satellite kinematics and the theoretical modelling of redshift-space distortions. We show that different galaxy selection criteria lead to noticeable differences in the radial distributions and velocity structure of satellite galaxies. Specifically, whereas samples of stel- lar mass selected galaxies feature satellites that roughly follow the dark matter, emission line satellite galaxies are located preferentially in the outskirts of halos and display net infall veloc- ities. We demonstrate that capturing these differences is crucial for modelling the multipoles of the correlation function in redshift space, even on large scales. In particular, we show how modelling small scale velocities with a single Gaussian distribution leads to a poor description of the measure clustering. In contrast, we propose a parametrization that is flexible enough to model the satellite kinematics, and that leads to and accurate description of the correlation function down to sub-Mpc scales. We anticipate that our model will be a necessary ingredient in improved theoretical descriptions of redshift space distortions, which together could result in a significantly tighter on cosmological constraints and more optimal exploitation of future large datasets.
Cosmic ray transport and radiative processes in nuclei of starburst galaxies

The high rate of star formation and supernova explosions of starburst galaxies make them interesting sources of high-energy radiation. Depending on the level of turbulence present in their interstellar medium, the bulk of cosmic rays produced inside starburst galaxies may lose most of their energy before escaping, thereby making these sources behave as calorimeters, at least up to some maximum energy. Contrary to previous studies, here we investigate in detail the conditions under which cosmic ray confinement may be effective for electrons and nuclei and we study the implications of cosmic ray confinement in terms of multifrequency emission from starburst nuclei and production of high-energy neutrinos. The general predictions are then specialized to three cases of active starbursts, namely, M82, NGC 253, and Arp220. Both primary and secondary electrons, as well as electron–positron pairs produced by gamma-ray absorption inside starburst galaxies are taken into account. Electrons and positrons produced as secondary products of hadronic interactions are found to be responsible for most of the emission of leptonic origin. In particular, synchrotron emission of very high energy secondary electrons produces an extended emission of hard X-rays that represents a very interesting signature of hadronic process in starburst galaxies, potentially accessible to current and future observations in the X-ray band. A careful understanding of both the production and absorption of gamma-rays in starburst galaxies is instrumental to the assessment of the role of these astrophysical sources as sources of high-energy astrophysical neutrinos.
An evaluation of the U.S. EPA's correction equation for PurpleAir sensor data in smoke, dust, and wintertime urban pollution events

Abstract. PurpleAir sensors (PASs) are low-cost tools to measure fine particulate matter (PM) concentrations and are now widely used, especially in regions with few regulatory monitors. However, the raw PAS data have significant biases, so the sensors must be calibrated to generate accurate data. The U.S. EPA recently developed a national correction equation and has integrated corrected PAS data onto its AirNow website. This integration results in much better spatial coverage for PM2.5 (particulate matter with diameters less than 2.5 µm) across the US. The goal of our study is to evaluate the EPA correction equation for three different types of aerosols: typical urban wintertime aerosol, smoke from biomass burning, and mineral dust. We identified 50 individual pollution events, each having a peak hourly PM2.5 concentration of at least 47 µg m−3 and a minimum of 3 h over 40 µg m−3 and characterized the primary aerosol type as either typical urban, smoke, or long-range transported dust. For each event, we paired a PAS sampling outside air with a nearby regulatory PM2.5 monitor to evaluate the agreement. All 50 events show statistically significant correlations (R values between 0.71–1.00) between the hourly PAS and regulatory data but with varying slopes. We then corrected the PAS data using either the correction equation from Barkjohn et al. (2021) or a new equation that is now being used by the U.S. EPA for the AirNow Fire and Smoke Map (U.S. EPA, 2022b). Both equations do a good job at correcting the data for smoke and typical pollution events but with some differences. Using the Barkjohn et al. (2021) equation, we find mean slopes of 1.00 and 0.99 for urban and smoke aerosol events, respectively, for the corrected data versus the regulatory data. For heavy smoke events, we find a small change in the slope at very high PM2.5 concentrations (> 600 µg m−3), suggesting a ∼ 20 % underestimate in the corrected PAS data at these extremely high concentrations. Using the new EPA equation, we find slopes of 0.95 and 0.88 for urban and smoke events, respectively, indicating a slight underestimate in PM2.5 using this equation, especially for smoke events. For dust events, while the PAS and regulatory data still show significant correlations, the PAS data using either correction equation underestimate the true PM2.5 by a factor of 5–6. We also examined several years of co-located regulatory and PAS data from a site near Owens Lake, California (CA), which experiences high concentrations of PM2.5 due to both smoke and locally emitted dust. For this site, we find similar results as above; the corrected PAS data are accurate in smoke but are too low by a factor of 5–6 in dust. Using these data, we also find that the ratios of PAS-measured PM10 / PM1 mass and 0.3 µm / 5 µm particle counts are significantly different for dust compared to smoke. Using this difference, we propose a modified correction equation that improves the PAS data for some dust events, but further work is needed to improve this algorithm.
AKRUAL: Jurnal Akuntansi

Whistleblowing has gained more attention worldwide. As many as 43% of fraudulent acts can be detected thanks to tips or whistleblowing. Graduates from the Accounting major are future auditors and accountants who are most likely to face illegal actions in their careers. This study aims to understand the factors that motivate undergraduate accounting students’ whistleblowing intention. This study explores how the factors of Consequence’s Magnitude (CM), Social Agreement (SA), Proximity (PX) and Fear of Retaliation (FR) can affect Whistleblowing Intention (WI). The results of this study indicate that the CM, SA, and PX factors have no significant effect on WI, while the FR factor has a significant effect on WI. This research is expected to positively contribute to assisting Lecturers of the Accounting Department in designing a curriculum to encourage undergraduate Accounting students to have stronger WI and be ready to be practised in the actual working environment. This research is also useful for future researcher who would like to explore the topic of whistleblowing intention.
Attenuation of Millimeter Emission from Circumstellar Disks Induced by the Rapid Dust Accretion

From millimeter observations of classical T Tauri stars, it is suggested that dust grains in circumstellar disks have grown to millimeter sizes or larger. However, gas drag on such large grains induces rapid accretion of the dust. We examine the evolution of dust disks composed of millimeter-sized grains and show that rapid accretion of the dust disk causes attenuation of millimeter continuum emission. If a dust disk is composed mainly of grains of 1 cm to 1 m, its millimeter emission goes off within 106 yr. Hence, grains in this size range cannot be the main population of the dust. Considering our results together with grain growth suggested by the millimeter continuum observations, we expect that the millimeter continuum emission of disks comes mainly from grains in a narrow size range of 1 mm to 1 cm. This suggests either that growth of millimeter-sized grains to centimeter size takes more than 106 yr or that millimeter-sized grains are continuously replenished. In the former case, planet formation is probably difficult, especially in the outer disks. In the latter case, reservoirs of millimeter grains are possibly large (≳10 m) bodies, which can reside in the disk more than 106 yr. Constraints on the grain growth timescale are discussed for the above two cases.