Miracle-dz/UniFAR-FTUs huggingface dataset:
How is the COVID-19 pandemic affecting cooperation?

Do crises bring people together or pull them apart? Here we examine how people’s willingness to help others and their perceived interdependence with others changed during the COVID-19 pandemic, and assess what factors are associated with any change. We collected data at 4 time points from the same cohort of 497 paid participants, starting on March 6th, before the pandemic was declared, through April 2. We found that perceived interdependence with neighbors and with humanity increased over time on multiple measures. However, regarding cooperation, agreement with the statement that helping someone in need “is the right thing to do” decreased over time (towards both a neighbor and a citizen of another country). Although the changes per time period were small for some of these effects, cumulatively they were non-trivial (ranging from a .33 to a .75 change on a 7 point likert scale). There was no change over time in participants' reported willingness to help somebody in their neighborhood (cooperation) or their feelings that when “All of humanity succeeds” they feel good (interdependence). We found reliable associations of change in cooperation and interdependence with sex, age, and pre-existing medical condition. We are collecting data on an ongoing basis which will allow us to investigate how these variables continue to change or not as the pandemic unfolds.
Epigenetic‐Based Mechanisms of Osteoblast Suppression in Multiple Myeloma Bone Disease

Multiple myeloma (MM) bone disease is characterized by the development of osteolytic lesions, which cause severe complications affecting the morbidity, mortality, and treatment of myeloma patients. Myeloma tumors seeded within the bone microenvironment promote hyperactivation of osteoclasts and suppression of osteoblast differentiation. Because of this prolonged suppression of bone marrow stromal cells’ (BMSCs) differentiation into functioning osteoblasts, bone lesions in patients persist even in the absence of active disease. Current antiresorptive therapy provides insufficient bone anabolic effects to reliably repair MM lesions. It has become widely accepted that myeloma‐exposed BMSCs have an altered phenotype with pro‐inflammatory, immune‐modulatory, anti‐osteogenic, and pro‐adipogenic properties. In this review, we focus on the role of epigenetic‐based modalities in the establishment and maintenance of myeloma‐induced suppression of osteogenic commitment of BMSCs. We will focus on recent studies demonstrating the involvement of chromatin‐modifying enzymes in transcriptional repression of osteogenic genes in MM‐BMSCs. We will further address the epigenetic plasticity in the differentiation commitment of osteoprogenitor cells and assess the involvement of chromatin modifiers in MSC‐lineage switching from osteogenic to adipogenic in the context of the inflammatory myeloma microenvironment. Lastly, we will discuss the potential of employing small molecule epigenetic inhibitors currently used in the MM research as therapeutics and bone anabolic agents in the prevention or repair of osteolytic lesions in MM. © 2019 The Authors. JBMR Plus published by Wiley Periodicals, Inc. on behalf of American Society for Bone and Mineral Research.
A PERTURBATION AND GENERIC SMOOTHNESS OF THE VAFA–WITTEN MODULI SPACES ON CLOSED SYMPLECTIC FOUR-MANIFOLDS

Abstract We prove a Freed–Uhlenbeck style generic smoothness theorem for the moduli space of solutions to the Vafa–Witten equations on a closed symplectic four-manifold by using a method developed by Feehan for the study of the PU(2)-monopole equations on smooth closed four-manifolds. We introduce a set of perturbation terms to the Vafa–Witten equations, and prove that the moduli space of solutions to the perturbed Vafa–Witten equations on a closed symplectic four-manifold for the structure group SU(2) or SO(3) is a smooth manifold of dimension zero for a generic choice of the perturbation parameters.
Combined effect of chitosan coating and modified atmosphere packaging on fresh‐cut cucumber

Abstract Fresh‐cut cucumber was coated with different concentrations of edible chitosan solutions and packaged in air‐, nitrogen‐, and argon‐based MA to preserve quality and extend shelf life. The effectiveness of individual and combined treatments on some quality parameters was examined at intervals during 12 days storage at a temperature of 5°C. The concentration of chitosan solutions significantly affected the performance of fresh‐cut cucumber in MA packages. Improved quality retention and reduced carbon dioxide production were observed in chitosan‐coated fresh‐cut samples. Argon‐based MA packaged samples exhibited better potential than air and nitrogen‐based MA packaging in retarding tissue respiration, physiological changes, chlorophyll degradation, and extending shelf life of fresh‐cut cucumber. Combined chitosan coating with MA packaging maintained quality, microbial safety, and extended the shelf life of fresh‐cut cucumber.
Market Access and Regional Dispersion of Human Capital Accumulation in Turkey

Building on the early advances in development economics, the theoretical construct of the New Economic Geography asserts that geography plays a crucial role in educational human capital accumulation. Based on this expectation, this study investigates the impact market access on provincial human capital accumulation in Turkey. Results indicate that market access matters for understanding why some regions lag behind others in terms of average years of schooling. Our results are robust to the inclusion of spatial mechanisms, different specifications of the spatial weight matrix, endogeneity and alternative measurements of market access and to a host of other factors that affect regional human capital accumulation.
Consistent cosmic shear in the face of systematics: a B-mode analysis of KiDS-450, DES-SV and CFHTLenS

We analyse three public cosmic shear surveys; the Kilo-Degree Survey (KiDS-450), the Dark Energy Survey (DES-SV) and the Canada France Hawaii Telescope Lensing Survey (CFHTLenS). Adopting the “COSEBIs” statistic to cleanly and completely separate the lensing E-modes from the non-lensing B-modes, we detect B-modes in KiDS-450 and CFHTLenS at the level of ∼2. 7σ. For DES-SV we detect B-modes at the level of 2. 8σ in a non-tomographic analysis, increasing to a 5. 5σB-mode detection in a tomographic analysis. In order to understand the origin of these detected B-modes we measure the B-mode signature of a range of different simulated systematics including PSF leakage, random but correlated PSF modelling errors, camera-based additive shear bias and photometric redshift selection bias. We show that any correlation between photometric-noise and the relative orientation of the galaxy to the point-spread-function leads to an ellipticity selection bias in tomographic analyses. This work therefore introduces a new systematic for future lensing surveys to consider. We find that the B-modes in DES-SV appear similar to a superposition of the B-mode signatures from all of the systematics simulated. The KiDS-450 and CFHTLenS B-mode measurements show features that are consistent with a repeating additive shear bias.
Capital Structure in U.S., a Quantile Regression Approach with Macroeconomic Impacts

The major perspective of this paper is to provide more evidence into the empirical determinants of capital structure adjustment in different macroeconomics states by focusing and discussing the relative importance of firm-specific and macroeconomic characteristics from an alternative scope in U.S. This study extends the empirical research on the topic of capital structure by focusing on a quantile regression method to investigate the behavior of firm-specific characteristics and macroeconomic variables across all quantiles of distribution of leverage (total debt, long-terms debt and short-terms debt). Thus, based on a partial adjustment model, we find that long-term and short-term debt ratios varying regarding their partial adjustment speeds; the short-term debt raises up while the long-term debt ratio slows down for same periods.
Nonseparable multinomial choice models in cross-section and panel data

Multinomial choice models are fundamental for empirical modeling of economic choices among discrete alternatives. We analyze identification of binary and multinomial choice models when the choice utilities are nonseparable in observed attributes and multidimensional unobserved heterogeneity with cross-section and panel data. We show that derivatives of choice probabilities with respect to continuous attributes are weighted averages of utility derivatives in cross-section models with exogenous heterogeneity. In the special case of random coefficient models with an independent additive effect, we further characterize that the probability derivative at zero is proportional to the population mean of the coefficients. We extend the identification results to models with endogenous heterogeneity using either a control function or panel data. In time stationary panel models with two periods, we find that differences over time of derivatives of choice probabilities identify utility derivatives "on the diagonal," i.e. when the observed attributes take the same values in the two periods. We also show that time stationarity does not identify structural derivatives "off the diagonal" both in continuous and multinomial choice panel models.
Testing the Number of Regimes in Markov Regime Switching Models

Markov regime switching models have been used in numerous empirical studies in economics and finance. However, the asymptotic distribution of the likelihood ratio test statistic for testing the number of regimes in Markov regime switching models has been an unresolved problem. This paper derives the asymptotic distribution of the likelihood ratio test statistic for testing the null hypothesis of $M_0$ regimes against the alternative hypothesis of $M_0 + 1$ regimes for any $M_0 \geq 1$ both under the null hypothesis and under local alternatives. We show that the contiguous alternatives converge to the null hypothesis at a rate of $n^{-1/8}$ in regime switching models with normal density. The asymptotic validity of the parametric bootstrap is also established.
Bayesian inference for stochastic differential equation mixed effects models of a tumour xenography study

We consider Bayesian inference for stochastic differential equation mixed effects models (SDEMEMs) exemplifying tumour response to treatment and regrowth in mice. We produce an extensive study on how an SDEMEM can be fitted by using both exact inference based on pseudo‐marginal Markov chain Monte Carlo sampling and approximate inference via Bayesian synthetic likelihood (BSL). We investigate a two‐compartments SDEMEM, corresponding to the fractions of tumour cells killed by and survived on a treatment. Case‐study data consider a tumour xenography study with two treatment groups and one control, each containing 5–8 mice. Results from the case‐study and from simulations indicate that the SDEMEM can reproduce the observed growth patterns and that BSL is a robust tool for inference in SDEMEMs. Finally, we compare the fit of the SDEMEM with a similar ordinary differential equation model. Because of small sample sizes, strong prior information is needed to identify all model parameters in the SDEMEM and it cannot be determined which of the two models is the better in terms of predicting tumour growth curves. In a simulation study we find that with a sample of 17 mice per group BSL can identify all model parameters and distinguish treatment groups.
Modal regression using kernel density estimation: A review

We review recent advances in modal regression studies using kernel density estimation. Modal regression is an alternative approach for investigating the relationship between a response variable and its covariates. Specifically, modal regression summarizes the interactions between the response variable and covariates using the conditional mode or local modes. We first describe the underlying model of modal regression and its estimators based on kernel density estimation. We then review the asymptotic properties of the estimators and strategies for choosing the smoothing bandwidth. We also discuss useful algorithms and similar alternative approaches for modal regression, and propose future direction in this field.
Quasi-oracle estimation of heterogeneous treatment effects

Flexible estimation of heterogeneous treatment effects lies at the heart of many statistical applications, such as personalized medicine and optimal resource allocation. In this article we develop a general class of two-step algorithms for heterogeneous treatment effect estimation in observational studies. First, we estimate marginal effects and treatment propensities to form an objective function that isolates the causal component of the signal. Then, we optimize this data-adaptive objective function. The proposed approach has several advantages over existing methods. From a practical perspective, our method is flexible and easy to use: in both steps, any loss-minimization method can be employed, such as penalized regression, deep neural networks, or boosting; moreover, these methods can be fine-tuned by cross-validation. Meanwhile, in the case of penalized kernel regression, we show that our method has a quasi-oracle property. Even when the pilot estimates for marginal effects and treatment propensities are not particularly accurate, we achieve the same error bounds as an oracle with prior knowledge of these two nuisance components. We implement variants of our approach based on penalized regression, kernel ridge regression, and boosting in a variety of simulation set-ups, and observe promising performance relative to existing baselines.
Set Identified Dynamic Economies and Robustness to Misspecification

We propose a new inferential methodology for dynamic economies that is robust to misspecification of the mechanism generating frictions. Economies with frictions are treated as perturbations of a frictionless economy that are consistent with a variety of mechanisms. We derive a representation for the law of motion for such economies and we characterize parameter set identification. We derive a link from model aggregate predictions to distributional information contained in qualitative survey data and specify conditions under which the identified set is refined. The latter is used to semi-parametrically estimate distortions due to frictions in macroeconomic variables. Based on these estimates, we propose a novel test for complete models. Using consumer and business survey data collected by the European Commission, we apply our method to estimate distortions due to financial frictions in the Spanish economy. We investigate the implications of these estimates for the adequacy of the standard model of financial frictions SW-BGG (Smets and Wouters (2007), Bernanke, Gertler, and Gilchrist (1999)).
Location of Siegel capture polynomials in parameter spaces

A cubic polynomial with a marked fixed point 0 is called an IS-capture polynomial if it has a Siegel disk D around 0 and if D contains an eventual image of a critical point. We show that any IS-capture polynomial is on the boundary of a unique bounded hyperbolic component of the polynomial parameter space determined by the rational lamination of the map and relate IS-capture polynomials to the cubic principal hyperbolic domain and its closure.
Waveform Selective Surfaces

The role of frequency is very important in electromagnetics since it may significantly change how a material interacts with an incident wave if the frequency spectrum varies. Here, a new kind of microwave window is demonstrated that has the unique property of controlling transmission and reflection based on not only the frequency of an incoming wave but also the waveform or pulse width. This is achieved by designing a planar periodic surface with circuit elements including diodes, which convert most of the incoming signal to zero frequency. This surface can preferentially pass or reject different kinds of signals, such as short pulses or continuous waves, even if they occur at the same frequency. Such a structure can be used, for example, to allow long communication signals to pass through, while rejecting short radar pulses in the same frequency band. It is related to the classic frequency selective surface, but adds the new dimension of waveform selectivity, which is possible only by introducing nonlinear electronics into the surface. Thus, the study is expected to provide new solutions to both fundamental and applied electromagnetic issues ranging from traditional antenna design and wireless communications to emerging areas such as cloaking, perfect lenses, and wavefront shaping.
Neural-networks for geophysicists and their application to seismic data interpretation

There has been a surge of interest in neural networks for the interpretation of seismic images over the last few years. Network-based learning methods can provide fast and accurate automatic interpretation, provided that there are many training labels. We provide an introduction to the field for geophysicists who are familiar with the framework of forward modeling and inversion. We explain the similarities and differences between deep networks and other geophysical inverse problems and show their utility in solving problems such as lithology interpolation between wells, horizon tracking, and segmentation of seismic images. The benefits of our approach are demonstrated on field data from the Sea of Ireland and the North Sea.
Do Men and Women Perceive Corruption Differently? Gender Differences in Perception of Need and Greed Corruption

Do men and women perceive corruption differently? While evidence suggest that there is a strong link between gender and corruption, and that gender differences can at least partly be derived from men and women having different attitudes towards corruption, most studies to date focus on gender differences in perceptions of the scale or severity of the corruption in general, rather than its different forms. However, we argue that factors such as role socialization, social status and life experiences may make men and women perceive different kinds of corruption. Drawing on the distinction between ‘need’ and ‘greed’ corruption, we suggest that women are more likely than men to perceive that corruption is driven by need rather than greed. In particular, women may be more likely to be exposed to need corruption because of their greater care taking responsibilities both in the professional and private sphere, and, much in line with marginalization theory, have easier access to forms of corruption that are less dependent upon embeddedness in collusive networks. Using unique survey data, we show that women and men indeed differ in their perceptions of need vs. greed, and that women perceive more need corruption, while men perceive more greed corruption. This suggests that perceptions of different forms of corruption are indeed gendered and we discuss the implication of this for anti-corruption policy.
Cryptic speciation in gentoo penguins is driven by geographic isolation and regional marine conditions: Unforeseen vulnerabilities to global change

The conservation of biodiversity is hampered by data deficiencies, with many new species and subspecies awaiting description or reclassification. Population genomics and ecological niche modelling offer complementary new tools for uncovering functional units of phylogenetic diversity. We hypothesize that phylogenetically delineated lineages of gentoo penguins (Pygoscelis papua) distributed across Antarctica and sub‐Antarctic Islands are subject to spatially explicit ecological conditions that have limited gene flow, facilitating genetic differentiation, and thereby speciation processes.
Tubastatin A inhibits HDAC and Sirtuin activity rather than being a HDAC6-specific inhibitor in mouse oocytes

Tubastatin A (TubA) is a highly selective histone deacetylase 6 (HDAC6) inhibitor. As expected, mouse germinal vesicle oocytes fail to extrude the first polar body following TubA treatment. However, a previous study demonstrated that homozygous Hdac6 knockout (KO) mice can be viable and fertile. Therefore, we asked whether TubA is indeed a specific inhibitor of HDAC6 activity. RNA-sequencing and in silico analysis demonstrated that the TubA-treated group presented significant changes in the expression of Hdac subfamily genes such as Hdac6, 10, and 11, and Sirtuin 2, 5, 6, and 7. Additionally, gene expression related to the p53, MAPK, Wnt, and Notch signaling pathways in the TubA-treated group were increased significantly; in contrast, gene expression related to metabolism, DNA replication, and oxidative phosphorylation was decreased significantly. Furthermore, gene expression related to cell cycle, cell structure, pyrimidine metabolism, pentose phosphate pathway, mitochondrial activation, proteasome pathway, RNA polymerase, DNA replication, cyclin-dependent kinase, nucleolar activity, and MI arrest were significantly decreased, indicating that TubA-induced abnormal meiotic maturation and oocyte senescence may be due to the combined effects of HDAC and Sirtuin inhibition, and not HDAC6 inhibition alone. Thus, we believed that this system could provide a model for monitoring the effects of TubA on mouse oocytes.
Faraday Rotation of Extended Emission as a Probe of the Large-Scale Galactic Magnetic Field

The Galactic magnetic field is an integral constituent of the interstellar medium (ISM), and knowledge of its structure is crucial to understanding Galactic dynamics. The Rotation Measures (RM) of extragalactic (EG) sources have been the basis of comprehensive Galactic magnetic field models. Polarised extended emission (XE) is also seen along lines of sight through the Galactic disk, and also displays the effects of Faraday rotation. Our aim is to investigate and understand the relationship between EG and XE RMs near the Galactic plane, and to determine how the XE RMs, a hitherto unused resource, can be used as a probe of the large-scale Galactic magnetic field. We used polarisation data from the Canadian Galactic Plane Survey (CGPS), observed near 1420 MHz with the Dominion Radio Astrophysical Observatory (DRAO) Synthesis Telescope. We calculated RMs from a linear fit to the polarisation angles as a function of wavelength squared in four frequency channels, for both the EG sources and the XE. Across the CGPS area, 55 ∘ < ℓ < 193 ∘ , − 3 ∘ < b < 5 ∘ , the RMs of the XE closely track the RMs of the EG sources, with XE RMs about half the value of EG-source RMs. The exceptions are places where large local HII complexes heavily depolarise more distant emission. We conclude that there is valuable information in the XE RM dataset. The factor of 2 between the two types of RM values is close to that expected from a Burn slab model of the ISM. This result indicates that, at least in the outer Galaxy, the EG and XE sources are likely probing similar depths, and that the Faraday rotating medium and the synchrotron emitting medium have similar variation with galactocentric distance.