Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Job Displacement on Earning, Mental Health and Mortality

Preliminary graphical evidence suggests that displacement leads to a substantial increase in hospitalization due to mental health problems and a dramatic increase in mortality in the year of displacement. On the other hand, there is some evidence that displacement leads to an increase in pregnancy-related health-care utilization, suggesting the importance of time in fertility decision.
Understanding Redundancy in Discrete Multi-Agent Communication

By providing agents with the capacity to learn sample-efficient and generalisable communications protocols, we may enable them to more effectively cooperate in real-world tasks. In this paper, we consider this in the context of discrete decentralised multi-agent reinforcement learning to provide insights into the impact of the often overlooked size of the message set. Within a referential game, we find that over-provisioning the message set size leads to improved sample efficiency, but that these policies tend to maintain a high-degree of redundancy, often utilising multiple messages to refer to each label in the dataset. We hypothesise that the additional redundancy within these converged policies may have implications for generalisation and experiment with methodologies to gradually reduce redundancy while maintaining sample efficiency. To this end, we propose a linearly-scheduled entropy regulariser which encourages an agent to initially maximise the utilisation of the available messages but, as training progresses, this incentive is removed. Through this mechanism, we achieve improved sample efficiency whilst converging to a model with significantly reduced redundancy and that generalises more effectively to previously unseen data.
AKRUAL: Jurnal AkuntansiVol 13, issue 2, April 2022p-ISSN: 2085-9643DOI: 10.26740/jajv13n2.p227-239 e-ISSN: 2502-6380 https://journal.unesa.ac.id/index.php/aj

Bad management practices that occur in the industry cause a lot of harm to many parties. Bad management practices occur due to managers' efforts to manipulate profits. Bad management practices that are carried out by management will be aggravated if the majority of shareholders participate to press the managers to make a profit manipulation so the earning quality becomes low. The purpose of this research is to find out how ownership concentration affects earnings quality and to determine the ability of directors to reduce the influence of ownership concentration on income quality. The research data used is a manufacturing company registered with the IDX in 2019-2020 with sampling methods using the target population method, that is, a sample determination technique using certain considerations. The data analysis method used is Moderated Regression Analysis (MRA). The results proved that the ownership concentration negatively affects the earning quality and board diversity can moderate the influence of ownership concentration on earning quality. Test results show the implication that Board Diversity can reduce the behavior of Ownership Concentration in performing earnings manipulation
Improved Unknown-Multiple Speaker clustering using HMM

In this report, we build up on our previous work on speaker clustering, where the number of speakers and segmentation boundaries are unknown a priori. We employ an ergodic HMM with minimum duration topology for this purpose. Starting from a large number of clusters in the beginning, we merge a pair of clusters in every iteration. A new criterion for the merging of two clusters is proposed, which ensures an increase in likelihood of the data. The merging is done in such a way that, the total number of parameters needed to model all the clusters remain same. Thus, the system finally achieves maximum likelihood (which was not the case in our last work) with the constant number of parameters. The merging process is repeated until there are no candidates available for merging. The efficiency and advantages of using only highly voiced frames was reported in our previous work, and we use the same features for this work. The system was evaluated on Hub-4 1996 evaluation set. Improvements over the previous work are reported and it is shown that, the system converges to right number of clusters in case of limited number of speakers.
Multi-adversarial Domain Generalization to Improve Face Recognition Reliability

Facial recognition is one of the most popular technologies nowadays, constituting the ﬁrst security barrier for devices like smartphones and tablets. This, in turn, makes facial recognition systems vulnerable to attacks with one of the most notorious being face presentation attacks. Face presentation attacks are an emerging threat and therefore have become more complex and unpredictable, through the years. The challenge of detecting face presentation attacks has led to the appearance of solutions based on liveness detection, facial appearance, contextual information, and more recently, solutions based on deep learning techniques. Within the deep learning ﬁeld, one topic that has been explored to recognize such attacks is the domain generalization topic. This work focuses on a solution that incorporates this topic. The adopted approach improves on an existing solution, taken as baseline, that trains a model with face presentation attacks seen in different conditions, to be able to generalize to other acquisition conditions. The present work proposes a source domain reorganization to enhance the generalized feature space, together with a modiﬁed triplet loss function that is more suitable for the proposed domain reorganization. The experiments were conducted on four public datasets. The solution proposed includes domain reorganization and a more suitable triplet loss function, achieving on-pair performance when tested with REPLAY-ATTACK dataset and outperforming the baseline architecture in the CASIA and MSU datasets. Future work includes complementing the proposed solution with a liveness detection algorithm, and a solution for addressing previously unseen attacks.
Journal Pre-proof Red blood cells protein profile is modified in breast cancer patients

Metastasis is the primary cause of death for most breast cancer patients who succumb to the disease. During the haematogenous dissemination, circulating tumor cells interact with different blood components. Thus, there are micro-environmental and systemic processes contributing to cancer regulation. We have recently published that Red Blood Cells (RBCs) that accompany circulating tumor cells have prognostic potential for metastatic breast cancer patients. Seemingly, RBCs are acquiring modifications in their proteomic composition that probably represents the systemic cancer disease, conditioned by the tumor microenvironment.
NaturalAdversaries: Can Naturalistic Adversaries Be as Effective as Artificial Adversaries?

While a substantial body of prior work has explored adversarial example generation for natural language understanding tasks, these examples are often unrealistic and diverge from the real-world data distributions. In this work, we introduce a two-stage adversarial example generation framework (NaturalAdversaries), for designing adversaries that are effective at fooling a given classifier and demonstrate natural-looking failure cases that could plausibly occur during in-the-wild deployment of the models. At the first stage a token attribution method is used to summarize a given classifier's behaviour as a function of the key tokens in the input. In the second stage a generative model is conditioned on the key tokens from the first stage. NaturalAdversaries is adaptable to both black-box and white-box adversarial attacks based on the level of access to the model parameters. Our results indicate these adversaries generalize across domains, and offer insights for future research on improving robustness of neural text classification models.
iCoLa: A Compositional Meta-language with Support for Incremental Language Development

Programming languages providing high-level abstractions can increase programmers’ productivity and program safety. Language-oriented programming is a paradigm in which domain-specific languages are developed to solve problems within specific domains with (high-level) abstractions relevant to those domains. However, language development involves complex design and engineering processes. These processes can be simplified by reusing (parts of) existing languages and by offering language-parametric tooling. In this paper we present iCoLa, a meta-language supporting incremental (meta-)programming based on reusable components. In our implementation of iCoLa, languages are first-class citizens, providing the full power of the host-language (Haskell) to compose and manipulate languages. We demonstrate iCoLa through the construction of the Imp, SIMPLE, and MiniJava languages via the composition and restriction of language fragments and demonstrate the variability of our approach through the construction of several languages using a fixed-set of operators.
BIOINFORMATICS expression A simple procedure for estimating the false discovery rate

Motivation: The most used criterion in microarray data analysis is nowadays the false discovery rate (FDR). In the framework of estimating procedures based on the marginal distribution of the P -values without any assumption on gene expression changes, estimators of the FDR are necessarily conservatively biased. Indeed, only an upper bound estimate can be obtained for the key quantity π 0 , which is the probability for a gene to be unmodiﬁed. In this paper, we propose a novel family of estimators for π 0 that allows the calculation of FDR. Results: The very simple method for estimating π 0 called LBE (Loca-tion Based Estimator) is presented together with results on its variability. Simulation results indicate that the proposed estimator performs well in ﬁnite sample and has the best mean square error in most of the casesascomparedwiththeproceduresQVALUE,BUMandSPLOSH. The different procedures are then applied to real datasets.
Quantum dark solitons in a Bose gas confined in a hard-wall box

Schrodinger equation for Bose gas with repulsive contact interactions in one-dimensional space may be solved analytically with the help of the Bethe ansatz if we impose periodic boundary conditions. It was shown that in such a system there exist many-body eigenstates directly corresponding to dark soliton solutions of the mean-field equation. The system is still integrable if one switches from the periodic boundary conditions to an infinite square well potential. The corresponding eigenstates were constructed by M. Gaudin. We analyze weak interaction limit of Gaudin's solutions and identify parametrization of eigenstates strictly connected with single and multiple dark solitons. Numerical simulations of detection of particle's positions reveal dark solitons in the weak interaction regime and their quantum nature in the presence of strong interactions.
Squeezed between shells? The origin of the Lupus I molecular cloud - APEX/LABOCA, Herschel, and Planck observations

B. Gaczkowski et al., “Squeezed between shells? The origin of the Lupus I molecular cloud APEX/LABOCA, Herschel, and Planck observations”, Astronomy & Astrophysics, Vol. 584, December 2015. This version of record is available online at: https://doi.org/10.1051/0004-6361/201526527 Reproduced with Permission from Astronomy and Astrophysics, © ESO, 2015
Elementary Signal Detection Theory

1. The signal-detection model 2. The equal-variance Gaussian model 3. Operating characteristics and the Gaussian model 4. Measures of detection performance 5. Confidence ratings 6. Forced-choice procedures 7. Discrimination and identification 8. Finite-state models 9. Likelihoods and likelihood ratios 10. Multidimensional stimuli 11. Statistical treatment A. A summary of probability theory References
The Abundance of Interstellar Nitrogen

Using the Hubble Space Telescope Goddard High Resolution Spectrograph (GHRS), we have obtained high S/N echelle observations of the weak interstellar N I λλ1160, 1161 absorption doublet toward the stars γ Cas, λ Ori, ι Ori, κ Ori, δ Sco, and κ Sco. In combination with a previous GHRS measurement of N I toward ζ Oph, these new observations yield a mean interstellar gas-phase nitrogen abundance (per 106 H atoms) of 106 N/H = 75 ± 4 (±1 σ). There are no statistically significant variations in the measured N abundances from sight line to sight line and no evidence of density-dependent nitrogen depletion from the gas phase. Since N is not expected to be depleted much into dust grains in these diffuse sight lines, its gas-phase abundance should reflect the total interstellar abundance. Consequently, the GHRS observations imply that the abundance of interstellar nitrogen (gas plus grains) in the local Milky Way is about 80% of the solar system value of 106 N/H = 93 ± 16. Although this interstellar abundance deficit is somewhat less than that recently found for oxygen and krypton with GHRS, the solar N abundance and the N I oscillator strengths are too uncertain to rule out definitively either a solar ISM N abundance or a solar ISM N abundance similar to that of O and Kr.
TESTING TRIGGERED STAR FORMATION IN SIX H ii REGIONS

We investigated six H ii regions with infrared, bright rimmed bubble or cometary morphology, in search of quantitative evidence for triggered star formation, both collect and collapse and radiatively driven implosion (RDI). We identified and classified 458 young stellar objects (YSOs) in and around the H ii regions. YSOs were determined by fitting a collection of radiative transfer model spectral energy distributions to infrared photometry for a large sample of point sources. We determined areas where there exist enhanced populations of relatively unevolved YSOs on the bright rims of these regions, suggesting that star formation has been triggered there. We further investigated the physical properties of the regions by using radio continuum emission as a proxy for ionizing flux powering the H ii regions, and 13CO (1–0) observations to measure masses and gravitational stability of molecular clumps. We used an analytical model of collect and collapse triggered star formation, as well as a simulation of RDI, and thus we compare the observed properties of the molecular gas with those predicted in the triggering scenarios. Notably, those regions in our sample that show evidence of cometary, or “blister,” morphology are more likely to show evidence of triggering.
Auger recombination of dark excitons in WS2 and WSe2 monolayers

We propose a novel phonon assisted Auger process unique to the electronic band structure of monolayer transition metal dichalcogenides (TMDCs), which dominates the radiative recombination of ground state excitons in tungsten based TMDCs. Using experimental and density functional theory computed values for the exciton energies, spin–orbit splittings, optical matrix element, and the Auger matrix elements, we find that the Auger process begins to dominate at carrier densities as low as 10 9 − 10 cm − 2 ? > , thus providing a plausible explanation for the low quantum efficiencies reported for these materials.
Evaluation of variance component estimators based on Henderson's Method

A two-way linear mixed model consisting of three variance components, � 2 1 ,� 2 2 and � 2 is applied to evaluate the performance of the modified variance component estimator obtained from Henderson’s (1953) method 3, developed by Al-Sarraj and von Rosen (2009). The estimator of interest � 2 1 , is obtained and modified, from two different partitions, (partition I and partition II), of the Henderson’s method 3 equations. By means of simulation, we evaluate the performance of these variance component estimators. The evaluation is in terms of mean square errors, estimated biases and probability of obtaining negative estimates. In addition, the comparison includes also variance component estimators obtained from likelihood-based procedures, REML and ML. The effect of imbalance and number of observations on mean square error is given. The modified Henderson’s method 3 variance component estimator obtained from partition I is recommended for values of � 2 2 /� 2 < 1.0. In terms of mean square errors and probability of obtaining negative estimates, the modified Henderson’s method 3 has achieved improvement over the corresponding non-modified ones. Further, unlike the likelihood-based estimators, the modified variance component estimators are non-iterative, and therefore computationally faster, with similar performance in terms of mean square error as the ML estimator.
Exploring the biases of a new method based on minimum variance for interplanetary magnetic clouds

Context. Magnetic clouds (MCs) are twisted magnetic structures ejected from the Sun and probed by in situ instruments. They are typically modeled as flux ropes (FRs). Aims. Magnetic field measurements are only available along the 1D spacecraft trajectory. The determination of the FR global characteristics requires the estimation of the FR axis orientation. Among the developed methods, the minimum variance (MV) is the most flexible, and features only a few assumptions. However, as other methods, MV has biases. We aim to investigate the limits of the method and extend it to a less biased method. Methods. We first identified the origin of the biases by testing the MV method on cylindrical and elliptical models with a temporal expansion comparable to the one observed in MCs. Then, we developed an improved MV method to reduce these biases. Results. In contrast with many previous publications we find that the ratio of the MV eigenvalues is not a reliable indicator of the precision of the derived FR axis direction. Next, we emphasize the importance of the FR boundaries selected since they strongly affect the deduced axis orientation. We have improved the MV method by imposing that the same amount of azimuthal flux should be present before and after the time of closest approach to the FR axis. We emphasize the importance of finding simultaneously the FR axis direction and the location of the boundaries corresponding to a balanced magnetic flux, so as to minimize the bias on the deduced FR axis orientation. This method can also define an inner flux-balanced sub-FR. We show that the MV results are much less biased when a compromize in size of this sub-FR is achieved. Conclusions. For weakly asymmetric field temporal profiles, the improved MV provides a very good determination of the FR axis orientation. The main remaining bias is moderate (lower than 6°) and is present mostly on the angle between the flux rope axis and the plane perpendicular to the Sun–Earth direction.
An Absolute Measurement of the Cosmic Microwave Background Radiation Temperature at 10.7 GHz

A balloon-borne experiment has measured the absolute temperature of the cosmic microwave background radiation (CMBR) at 10.7 GHz to be TCMBR = 2.730 ± 0.014 K. The error is the quadratic sum of several systematic errors, with a statistical error of less than 0.1 mK. The instrument is made up of a cooled corrugated horn antenna coupled to a total power radiometer. A cryogenic mechanical waveguide switch alternately connects the radiometer to the horn and to an internal reference load. The small measured temperature difference (≲20 mK) between the sky signal and the reference load in conjunction with the use of a cold front end keeps systematic instrumental corrections small. Atmospheric and window emission are minimized by flying the instrument at 24 km altitude. A large outer ground screen and smaller inner screen shield the instrument from stray radiation from the ground and the balloon. In-flight tests constrain the magnitude of ground radiation contamination, and low-level interference is monitored through observations in several narrow-frequency bands.
Signatures of midlatitude heat waves in global Rossby wave spectra

The paper investigates systematic changes of the global atmospheric circulation during midlatitude heat waves. The global balanced circulation is deﬁned in terms of the Rossby wave solutions of the linearized primitive equations. The circulation variability is assessed by the probability density functions (PDFs) of the normalized total energy anomalies with respect to their climatological values. The evaluation is performed in wavenumber space deﬁned by the zonal wavenumbers, meridional modes and vertical structure functions. Heat waves are deﬁned by spatially averaged surface temperatures in Eurasia 5 (bounded by the Ural) above the 95 % percentile on at least three consecutive days. Normalized energy anomalies of the Rossby waves are found to be χ 2 -distributed with a skewness associated with the number of degrees of freedom. The PDFs of energy anomalies during heat waves are compared with their climatological distributions for the zonal mean ﬂow, for the planetary and for the synoptic scales. During heat waves, the skewness of PDFs of planetary-scale circulation is increased up to a factor of two. The increase is associated with a drastic reduction of the number of degrees of freedom down to 1 / 4 compared to 10 climatology. This reduction explains the coarse structure of blocking events in the midlatitude troposphere as conﬁrmed by the reconstructed circulation in physical space. The changes in variability are also assessed by investigating submonthly circulation variance across scales. Planetary waves are found to be more persistent during heat waves, while the synoptic waves vary more, which is consistent with the idea of circulation blocking during the extreme heat events. The presented diagnostics can be applied for other extreme events in the atmosphere.
Primary Care Clinicians’ Perceived Role in Addressing Childhood Obesity in the Southern United States

Despite clear guidelines, evidence suggests that pediatric primary care clinicians often do not conduct weight assessments or engage pediatric patients and their families in discussions about weight management. This article investigates pediatric clinicians’ perceptions of their role in preventing and treating childhood obesity in primary care settings. Abstract Objectives Primary care is an opportune setting to promote healthy behaviors for children and families. In 2007, an expert committee recommended that pediatric primary care clinicians assess nutrition and physical activity at wellness visits and offer recommendations; however, little is known about what pediatric primary care clinicians perceive their role as in childhood weight management. This qualitative study aimed to describe the perceived role of pediatric primary care clinicians in the prevention and treatment of childhood obesity in South Carolina, a state in the southern United States with high rates of childhood obesity. Methods Pediatric primary care clinicians (n = 23) from South Carolina were recruited for two focus groups. Participants were asked semistructured, open-ended questions, and audio recordings were transcribed verbatim. Themes and subthemes were identified through an iterative coding and consensus-building process with two coders. Excerpts coded under the parent code of “clinician role” centered on three themes: conducting assessments, making referrals, and providing education. Results Pediatric primary care clinicians in South Carolina coalesced around the important role of addressing childhood obesity within primary care. Notably, clinicians primarily discussed treatment rather than prevention strategies and described changes in the scope of their practice over time as a result of the increasing numbers of pediatric patients with obesity. Conclusions Addressing childhood obesity within primary care is a critical component of obesity prevention and treatment in the southern United States. Effective, sustainable prevention and treatment within primary care will depend on the involvement of pediatric clinicians, thus emphasizing the importance of understanding how they perceive their role within this setting.