Miracle-dz/UniFAR-FTUs huggingface dataset:
Differential personality change earlier and later in the coronavirus pandemic in a longitudinal sample of adults in the United States

Five-factor model personality traits (neuroticism, extraversion, openness, agreeableness, conscientiousness) are thought to be relatively impervious to environmental demands in adulthood. The coronavirus pandemic is an unprecedented opportunity to examine whether personality changed during a stressful global event. Surprisingly, two previous studies found that neuroticism decreased early in the pandemic, whereas there was less evidence for change in the other four traits during this period. The present research used longitudinal assessments of personality from the Understanding America Study (N = 7,109; 18,623 assessments) to examine personality changes relatively earlier (2020) and later (2021–2022) in the pandemic compared to pre-pandemic levels. Replicating the two previous studies, neuroticism declined very slightly in 2020 compared to pre-pandemic levels; there were no changes in the other four traits. When personality was measured in 2021–2022, however, there was no significant change in neuroticism compared to pre-pandemic levels, but there were significant small declines in extraversion, openness, agreeableness, and conscientiousness. The changes were about one-tenth of a standard deviation, which is equivalent to about one decade of normative personality change. These changes were moderated by age and Hispanic/Latino ethnicity, but not race or education. Strikingly, younger adults showed disrupted maturity in that they increased in neuroticism and declined in agreeableness and conscientiousness. Current evidence suggests the slight decrease in neuroticism early in the pandemic was short-lived and detrimental changes in the other traits emerged over time. If these changes are enduring, this evidence suggests population-wide stressful events can slightly bend the trajectory of personality, especially in younger adults.
Air entrainment in dynamic wetting: Knudsen effects and the influence of ambient air pressure

Recent experiments on coating flows and liquid drop impact both demonstrate that wetting failures caused by air entrainment can be suppressed by reducing the ambient gas pressure. Here, it is shown that non-equilibrium effects in the gas can account for this behaviour, with ambient pressure reductions increasing the mean free path of the gas and hence the Knudsen number $\mathit{Kn}$ . These effects first manifest themselves through Maxwell slip at the boundaries of the gas, so that for sufficiently small $\mathit{Kn}$ they can be incorporated into a continuum model for dynamic wetting flows. The resulting mathematical model contains flow structures on the nano-, micro- and millimetre scales and is implemented into a computational platform developed specifically for such multiscale phenomena. The coating flow geometry is used to show that for a fixed gas–liquid–solid system (a) the increased Maxwell slip at reduced pressures can substantially delay air entrainment, i.e. increase the ‘maximum speed of wetting’, (b) unbounded maximum speeds are obtained, as the pressure is reduced only when slip at the gas–liquid interface is allowed for, and (c) the observed behaviour can be rationalised by studying the dynamics of the gas film in front of the moving contact line. A direct comparison with experimental results obtained from a dip-coating process shows that the model recovers most trends but does not accurately predict some of the high viscosity data at reduced pressures. This discrepancy occurs because the gas flow enters the ‘transition regime’, so that more complex descriptions of its non-equilibrium nature are required. Finally, by collapsing onto a master curve experimental data obtained for drop impact in a reduced pressure gas, it is shown that the same physical mechanisms are also likely to govern splash suppression phenomena.
Morphometric analysis of the elasmobranch olfactory rosette

The olfactory rosettes of elasmobranchs vary in shape and structure among species, but the functional consequences of this diversity are unresolved. Our goal was to quantify rosette morphology on dissected as well as diffusible iodine‐based contrast‐enhanced computed tomography (diceCT)‐imaged specimens to analyze the drivers of observed trends in a phylogenetic context and compare the methodologies. We hypothesized that lamellar count and rosette shape (fineness ratio) would not scale with animal size, but other rosette size variables would scale positively. We dissected rosettes from 14 elasmobranch species and collected morphometric data (fineness ratio, lamellar count, interlamellar distance, lamellar thickness, and raphe width). A subset of rosettes (five species) was used to analyze the effects of body size, while all 14 species were used for a phylogenetic principal component analysis (pPCA). We found that fineness ratio and lamellar counts varied significantly among species, and were positively correlated. The first two principal components of the pPCA explained 82% of the variation, with fineness ratio and lamellar count contributing most to the loadings, respectively. DiceCT was used for in situ imaging of four species of Carcharhiniformes. There were no significant differences between rosette structure or volume when comparing values from dissected specimens to values from in situ specimens obtained using diceCT. We also quantified the volume of the excurrent channel in the olfactory capsule. These data add to our understanding of how olfactory organ shape varies among species and can be used to create three‐dimensional models for future olfactory hydrodynamic studies.
Partisan bias in false memories for misinformation about the 2021 U.S. Capitol riot

ABSTRACT Memory for events can be biased. For example, people tend to recall more events that support than oppose their current worldview. The present study examined partisan bias in memory for events related to the January 6, 2021, Capitol riot in the United States. Participants rated their memory for true and false events that were either favourable to their political party or the other major political party in the United States. For both true and false events, participants remembered more events that favoured their political party. Regression analyses showed that the number of false memories that participants reported was positively associated with their tendency to support conspiracy beliefs and with their self-reported engagement with the Capitol riot. These results suggest that Democrats and Republicans remember the Capitol Riot differently and that certain individual difference factors can predict the formation of false memories in this context. Misinformation played an influential role in the Capitol riot and understanding differences in memory for this event is beneficial to avoiding similar tragedies in the future.
Measuring the accretion rate and kinetic luminosity functions of supermassive black holes

We derive accretion rate functions (ARFs) and kinetic luminosity functions (KLFs) for jet-launching supermassive black holes. The accretion rate as well as the kinetic power of an active galaxy is estimated from the radio emission of the jet. For compact low-power jets, we use the core radio emission while the jet power of high-power radio-loud quasars is estimated using the extended low-frequency emission to avoid beaming effects. We find that at low luminosities the ARF derived from the radio emission is in agreement with the measured bolometric luminosity function (BLF) of active galactic nucleus (AGN), i.e. all low-luminosity AGN launch strong jets. We present a simple model, inspired by the analogy between X-ray binaries (XRBs) and AGN, that can reproduce both the measured ARF of jet-emitting sources as well as the BLF. The model suggests that the break in power-law slope of the BLF is due to the inefficient accretion of strongly sub-Eddington sources. As our accretion measure is based on the jet power it also allows us to calculate the KLF and therefore the total kinetic power injected by jets into the ambient medium. We compare this with the kinetic power output from supernova remnants (SNRs) and XRBs, and determine its cosmological evolution.
Public views on the Covid‐19 immunity certificate: A scoping review

Already in its first implementation, the introduction of the Covid‐19 immunity certificate has generated some debate among the public. This debate might be a hindrance to the effective realization of this policy. This study aimed to systematically review published research evaluating public feeling of the Covid‐19 immunity certificate policy measure and to find which factors might influence its acceptance.
Impact of multiple substance use on circulating ST2, a biomarker of adverse cardiac remodelling, in women

ABSTRACT Context Cardiovascular disease (CVD) and heart failure (HF) are major causes of mortality in low-income populations and differ by sex. Risk assessment that incorporates cardiac biomarkers is common. However, research evaluating the utility of biomarkers rarely includes controlled substances, which may influence biomarker levels and thus influence CVD risk assessment. Materials and Methods We identified the effects of multiple substances on soluble “suppression of tumorigenicity 2” (sST2), a biomarker of adverse cardiac remodelling, in 245 low-income women. Adjusting for CVD risk factors, we examined associations between substance use and sST2 over six monthly visits. Results Median age was 53 years and 74% of participants were ethnic minority women. An sST2 level > 35 ng/mL (suggesting cardiac remodelling) during ≥1 study visit was observed in 44% of participants. In adjusted analysis, higher sST2 levels were significantly and positively associated with the presence of cocaine (Adjusted Linear Effect [ALE]:1.10; 95% CI:1.03-1.19), alcohol (ALE:1.10; 95% CI:1.04-1.17), heroin (ALE:1.25; 95% CI:1.10-1.43), and the interaction between heroin and fentanyl use. Conclusion Results suggest that the use of multiple substances influences the level of sST2, a biomarker often used to evaluate cardiovascular risk. Incorporating substance use alongside cardiac biomarkers may improve CVD risk assessment in vulnerable women.
Neural Global Illumination: Interactive Indirect Illumination Prediction Under Dynamic Area Lights

We propose neural global illumination, a novel method for fast rendering full global illumination in static scenes with dynamic viewpoint and area lighting. The key idea of our method is to utilize a deep rendering network to model the complex mapping from each shading point to global illumination. To efficiently learn the mapping, we propose a neural-network-friendly input representation including attributes of each shading point, viewpoint information, and a combinational lighting representation that enables high-quality fitting with a compact neural network. To synthesize high-frequency global illumination effects, we transform the low-dimension input to higher-dimension space by positional encoding and model the rendering network as a deep fully-connected network. Besides, we feed a screen-space neural buffer to our rendering network to share global information between objects in the screen-space to each shading point. We have demonstrated our neural global illumination method in rendering a wide variety of scenes exhibiting complex and all-frequency global illumination effects such as multiple-bounce glossy interreflection, color bleeding, and caustics.
Discovery and characterization of detached M dwarf eclipsing binaries in the WFCAM Transit Survey

We report the discovery of 16 detached M-dwarf eclipsing binaries with J < 16 mag and provide a detailed characterisation of three of them, using high-precision infrared light curves from the WFCAM Transit Survey (WTS). Such systems provide the most accurate and model-independent method for measuring the fundamental parameters of these poorly understood yet numerous stars, which currently lack sufficient observations to precisely calibrate stellar evolution models. We fully solve for the masses and radii of three of the systems, finding orbital periods in the range 1.5 < P < 4.9 days, with masses spanning 0.35 0.50M⊙ and radii between 0.38 0.50R⊙, with uncertainties of � 3.5 6.4% in mass and � 2.7 5.5% in radius. Close-companions in short-period binaries are expected to be tidally-locked into fast rotational velocities, resulting in high levels of magnetic activity. This is predicted to inflate their radii by inhibiting convective flow and increasing star spot coverage. The radii of the WTS systems are inflated above model predictions by � 3 12%, in agreement with the observed trend, despite an expected lower systematic contribution from star spots signals at infrared wavelengths. We searched for correlation between the orbital period and radius inflation by combining our results with all existing M-dwarf radius measurements of comparable precision, but we found no statistically significant evidence for a decrease in radius inflation for longer period, less active systems. Radius inflation continues to exists in non-synchronised systems indicating that the problem remains even for very low activity M-dwarfs. Resolving this issue is vital not only for understanding the most populous stars in the Universe, but also for characterising their planetary companions, which hold the best prospects for finding Earth-like planets in the traditional habitable zone.
Immunotherapy combined with chemotherapy versus chemotherapy alone as the first‐line treatment of PD‐L1‐negative and driver‐gene‐negative advanced nonsquamous non‐small‐cell lung cancer: An updated systematic review and meta‐analysis

This meta‐analysis aimed to compare the efficacy of immunotherapy combined with chemotherapy versus chemotherapy alone as the first‐line therapy for patients with programmed death ligand‐1 (PD‐L1)‐negative and driver‐gene‐negative advanced nonsquamous non‐small‐cell lung cancer (NSCLC).
RegBR: A novel Brazilian government framework to classify and analyze industry-specific regulations

Government transparency and openness are key factors to bring forth the modernization of the state. The combination of transparency and digital information has given rise to the concept of Open Government, that increases citizen understanding and monitoring of government actions, which in turn improves the quality of public services and of the government decision making process. With the goal of improving legislative transparency and the understanding of the Brazilian regulatory process and its characteristics, this paper introduces RegBR, the first national framework to centralize, classify and analyze regulations from the Brazilian government. A centralized database of Brazilian federal legislation built from automated ETL routines and processed with data mining and machine learning techniques was created. Our framework evaluates different NLP models in a text classification task on our novel Portuguese legal corpus and performs regulatory analysis based on metrics that concern linguistic complexity, restrictiveness, law interest, and industry-specific citation relevance. Our results were examined over time and validated by correlating them with known episodes of regulatory changes in Brazilian history, such as the implementation of new economic plans or the emergence of an energy crisis. Methods and metrics proposed by this framework can be used by policy makers to measure their own work and serve as inputs for future studies that could analyze government changes and their relationship with federal regulations.
Evaluation of Predictive Motor Control With Two Touchscreen Tablet-Based Tests: Reliability and Validity in School-Aged Children

As predictive motor control is an important index of neuromotor development and maturation, we developed two touchscreen tablet-based tests of this function. Our aim was to investigate the reliability and validity of both a rapid manual interception test and a pursuit tracking test, using a sample of 124 children (62 boys and 62 girls) from two age groups (7-8-year-oldss and 9–10-year-olds). Participants performed both tablet tests with a stylus (sample rate 100 Hz) with both a visible and a temporarily invisible moving target. Confirmatory factor analyses and omega coefficients showed that both tests were univariate methods that provided a reliable assessment of the latent factor related to predictive visuomotor control. As would be expected, compared to younger children, older children performed better on both manual interception and pursuit tracking. The correlations between the latent factors of the two tests at 95% confidence intervals (−.276, −.608) suggested shared variance. Thus, the touchscreen-tablet based tests of rapid manual interception and manual pursuit tracking appear psychometrically suitable for assessing the neuromotor ability of predictive control in 7-10-year-old children.
Construct Validation and Normative Data for Different Versions of the Shirom-Melamed Burnout Questionnaire/Measure in a Swedish Population Sample.

The overall aim of the present study was to examine the construct validity of different versions of the Shirom-Melamed Burnout Questionnaire/Measure (SMBQ/M) suggested in previous work, as well as to provide normative data for a large population-based sample in Sweden with a broad range in age. Cross-sectional data from the Västerbotten Environmental Health Study in Sweden were used. The 3406 participants (56 % women) in this study, aged 18 to 79 years, constituted a random sample stratified for age and sex. Participants responded to a questionnaire including the 4 factor 22-item version of the SMBM as well as background questions and a number of validated questionnaire instruments assessing e.g. sleep disturbance, depression, anxiety, perceived stress, and somatic symptoms. The dimensionality of different versions of the SMBM were examined with confirmatory factor analysis. A modified 4-factor 19-item model of the SMBM provided good model-fit, and two 2-factor models (11-item and 6-item) provided excellent model fit. The relationships to relevant psychological constructs provided support for convergent validity for the suggested versions of the SMBM. Finally, normative data were obtained for a broad age group for the different versions. In conclusion, we suggest that for assessing the core of the burnout construct in terms of emotional and physical exhaustion and cognitive weariness, the SMBM-11 or SMBM-6 for repeated measures, are to be used. For a broader assessment of burnout incorporating both symptoms and information about the process of exhaustion via the subscales of listlessness and tension, we recommend the use of the modified 4-factor SMBM-19. This article is protected by copyright. All rights reserved.
Publication Bias in Asset Pricing Research

Researchers are more likely to share notable findings. As a result, published findings tend to overstate the magnitude of real-world phenomena. This bias is a natural concern for asset pricing research, which has found hundreds of return predictors and little consensus on their origins. Empirical evidence on publication bias comes from large scale meta-studies. Meta-studies of cross-sectional return predictability have settled on four stylized facts that demonstrate publication bias is not a dominant factor: (1) almost all findings can be replicated, (2) predictability persists out-of-sample, (3) empirical $t$-statistics are much larger than 2.0, and (4) predictors are weakly correlated. Each of these facts has been demonstrated in at least three meta-studies. Empirical Bayes statistics turn these facts into publication bias corrections. Estimates from three meta-studies find that the average correction (shrinkage) accounts for only 10 to 15 percent of in-sample mean returns and that the risk of inference going in the wrong direction (the false discovery rate) is less than 10%. Meta-studies also find that $t$-statistic hurdles exceed 3.0 in multiple testing algorithms and that returns are 30 to 50 percent weaker in alternative portfolio tests. These facts are easily misinterpreted as evidence of publication bias effects. We clarify these misinterpretations and others, including the conflating of ``mostly false findings'' with ``many insignificant findings,'' ``data snooping'' with ``liquidity effects,'' and ``failed replications'' with ``insignificant ad-hoc trading strategies. '' Meta-studies outside of the cross-sectional literature are rare. The four facts from cross-sectional meta-studies provide a framework for future research. We illustrate with a preliminary re-examination of equity premium predictability.
MONSTERS, BLACK HOLES AND THE STATISTICAL MECHANICS OF GRAVITY

We review the construction of monsters in classical general relativity. Monsters have finite ADM mass and surface area, but potentially unbounded entropy. From the curved space perspective, they are objects with large proper volume that can be glued on to an asymptotically flat space. At no point is the curvature or energy density required to be large in Planck units, and quantum gravitational effects are, in the conventional effective field theory framework, small everywhere. Since they can have more entropy than a black hole of equal mass, monsters are problematic for certain interpretations of black hole entropy and the AdS/CFT duality. In the second part of the paper we review recent developments in the foundations of statistical mechanics which make use of properties of high-dimensional (Hilbert) spaces. These results primarily depend on kinematics — essentially, the geometry of Hilbert space — and are relatively insensitive to dynamics. We discuss how this approach might be adopted as a basis for the statistical mechanics of gravity. Interestingly, monsters and other highly entropic configurations play an important role.
Entanglement negativity in a fermionic chain with dissipative defects: exact results

We investigate the dynamics of the fermionic logarithmic negativity in a free-fermion chain with a localized loss, which acts as a dissipative impurity. The chain is initially prepared in a generic Fermi sea. In the standard hydrodynamic limit of large subsystems and long times, with their ratio fixed, the negativity between two subsystems is described by a simple formula, which depends only on the effective absorption coefficient of the impurity. The negativity grows linearly at short times, then saturating to a volume-law scaling. Physically, this reflects the continuous production with time of entangling pairs of excitations at the impurity site. Interestingly, the negativity is not the same as the Rényi mutual information with Rényi index 1/2 , in contrast with the case of unitary dynamics. This reflects the interplay between dissipative and unitary processes. The negativity content of the entangling pairs is obtained in terms of an effective two-state mixed density matrix for the subsystems. Criticality in the initial Fermi sea is reflected in the presence of logarithmic corrections. The prefactor of the logarithmic scaling depends on the loss rate, suggesting a nontrivial interplay between dissipation and criticality.