Notes

Executive regarding Vegetation regarding Effective Output of Therapeutics.
We also find notable asymmetric effects of positive and negative interest rate shocks in the Brazilian economy, with positive interest rate shocks affecting more financial stability. Finally, our results also suggest a non-linear relationship between interest rate changes and financial stability, reinforcing the need to mitigate monetary policy shocks through interest rate smoothing and adequate communication and transparency to society.We run an experiment to study the effects of Covid-19 lockdown in Italy on preferences for fairness and cooperation. Given the impossibility of having participants in the lab during the lockdown, we adopted an online methodology based on a multi-platform architecture that brings experimental subjects in a "Lab on the Web". Results from standard Ultimatum and linear Public Good games show that the circumstances in which participants lived the lockdown significantly affect their behavior in the two games. In particular, participants are more selfish in the ultimatum bargaining and contribute more to the public good when social isolation is stronger. However, cooperation decreases when lockdown is longer. We interpret these results as evidence of "social embeddedness" to compensate for "social distancing".Random-effects meta-analyses of observational studies can produce biased estimates if the synthesized studies are subject to unmeasured confounding. We propose sensitivity analyses quantifying the extent to which unmeasured confounding of specified magnitude could reduce to below a certain threshold the proportion of true effect sizes that are scientifically meaningful. We also develop converse methods to estimate the strength of confounding capable of reducing the proportion of scientifically meaningful true effects to below a chosen threshold. These methods apply when a "bias factor" is assumed to be normally distributed across studies or is assessed across a range of fixed values. Our estimators are derived using recently proposed sharp bounds on confounding bias within a single study that do not make assumptions regarding the unmeasured confounders themselves or the functional form of their relationships with the exposure and outcome of interest. We provide an R package, EValue, and a free website that compute point estimates and inference and produce plots for conducting such sensitivity analyses. These methods facilitate principled use of random-effects meta-analyses of observational studies to assess the strength of causal evidence for a hypothesis.Radiomics involves the study of tumor images to identify quantitative markers explaining cancer heterogeneity. The predominant approach is to extract hundreds to thousands of image features, including histogram features comprised of summaries of the marginal distribution of pixel intensities, which leads to multiple testing problems and can miss out on insights not contained in the selected features. In this paper, we present methods to model the entire marginal distribution of pixel intensities via the quantile function as functional data, regressed on a set of demographic, clinical, and genetic predictors to investigate their effects of imaging-based cancer heterogeneity. We call this approach quantile functional regression, regressing subject-specific marginal distributions across repeated measurements on a set of covariates, allowing us to assess which covariates are associated with the distribution in a global sense, as well as to identify distributional features characterizing these differences, includisity distribution between males and females and between tumors with and without DDIT3 mutations.We design and test the hypothesis that for energy firms' oil market activities impact capital structure. Using a unique sample of 726 energy firms from 56 countries, we find that oil market activities do influence capital structure. The speed of adjustment (SOA) to leverage when not exposed to oil market activities is between 27.5 and 66.4%. When exposed to oil price growth (market liquidity) the corresponding SOA is between 51.1 and 72.4% (40.9-76.1%). We conclude that oil price growth slows down while market liquidity improves SOA to leverage for energy firms. By comparison, using a sample of over 32,000 non-energy firms from 108 countries, we find no evidence that oil market activities dictate capital structure.During the current century, each major coronavirus outbreak has triggered a quick and immediate surge of academic publications on its respective topic. DDR1-IN-1 ic50 The spike in research publications following the 2019 Novel Coronavirus (Covid-19) outbreak, however, has been like no other. The global crisis caused by the Covid-19 pandemic has mobilised scientific efforts at an unprecedented scale. In less than 5 months, more than 12,000 research items and in less than seven months, more than 30,000 items were indexed, while it is projected that the number could exceed 80,000 by the end of 2020, should the current trend continues. With the health crisis affecting all aspects of life, research on Covid-19 seems to have become a focal point of interest across many academic disciplines. Here, scientometric aspects of the Covid-19 literature are analysed and contrasted with those of the two previous major coronavirus diseases, i.e., Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS). The focuses also display the involvement of authors from a broader variety of countries compared to SARS and MERS. Considering the speed at which the Covid-19-related literature is accumulating, an interesting dimension that warrants further exploration could be to assess if the quality and rigour of these publications have been affected.New sources of citation data have recently become available, such as Microsoft Academic, Dimensions, and the OpenCitations Index of CrossRef open DOI-to-DOI citations (COCI). Although these have been compared to the Web of Science Core Collection (WoS), Scopus, or Google Scholar, there is no systematic evidence of their differences across subject categories. In response, this paper investigates 3,073,351 citations found by these six data sources to 2,515 English-language highly-cited documents published in 2006 from 252 subject categories, expanding and updating the largest previous study. Google Scholar found 88% of all citations, many of which were not found by the other sources, and nearly all citations found by the remaining sources (89-94%). A similar pattern held within most subject categories. Microsoft Academic is the second largest overall (60% of all citations), including 82% of Scopus citations and 86% of WoS citations. In most categories, Microsoft Academic found more citations than Scopus and WoS (182 and 223 subject categories, respectively), but had coverage gaps in some areas, such as Physics and some Humanities categories.
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