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Structure, Submitting, Compound Make up, along with Gene Term Pattern of Glandular Trichomes on the Foliage involving Rhus potaninii Maxim.
We aim to explain the unadjusted, adjusted and marginal number needed to treat (NNT) and provide software for clinicians to compute them.

The NNT is an efficacy index that is commonly used in randomised clinical trials. The NNT is the average number of patients needed to treat to obtain one successful outcome (ie, response) due to treatment. We developed the nntcalc R package for desktop use and extended it to a user-friendly web application. We provided users with a user-friendly step-by-step guide. The application calculates the NNT for various models with and without explanatory variables. The implemented models for the adjusted NNT are linear regression and analysis of variance (ANOVA), logistic regression, Kaplan-Meier and Cox regression. If no explanatory variables are available, one can compute the unadjusted Laupacis
's NNT, Kraemer and Kupfer's NNT and the Furukawa and Leucht's NNT. All NNT estimators are computed with their associated appropriate 95% confidence intervals. All calculations are in R and are replicable.

The application provides the user with an easy-to-use web application to compute the NNT in different settings and models. We illustrate the use of the application from examples in schizophrenia research based on the Positive and Negative Syndrome Scale. The application is available from https//nntcalc.iem.technion.ac.il. The output is given in a journal compatible text format, which users can copy and paste or download in a comma-separated values format.

This application will help researchers and clinicians assess the efficacy of treatment and consequently improve the quality and accuracy of decisions.
This application will help researchers and clinicians assess the efficacy of treatment and consequently improve the quality and accuracy of decisions.Although a safe and effective vaccine holds the greatest promise for resolving the COVID-19 pandemic, hesitancy to accept vaccines remains common. To explore vaccine acceptance decisions, we conducted a national survey of 1,000 people from all US states in August of 2020 and a replication in December of 2020. Using a 3 × 3 × 3 factorial experimental design, we estimated the impact of three factors probability of 1) protection against COVID-19, 2) minor side effects, and 3) a serious adverse reactions. The outcome was respondents' reported likelihood of receiving a vaccine for the coronavirus. Probability of vaccine efficacy (50%, 70%, or 90%) had the largest effect among the three factors. Microbiology inhibitor The probability of minor side effects (50%, 75%, 90%) including fever and sore arm, did not significantly influence likelihood of receiving the vaccine. The chances of a serious adverse reaction, such as temporary or permanent paralysis, had a small but significant effect. A serious adverse reaction rate of 1/100,000 was more likely to discourage vaccine use in comparison to rates of 1/million or 1/100 million. All interactions between the factors were nonsignificant. A replication following the announcement that vaccines were 95% effective showed small, but significant increases in the likelihood of taking a vaccine. The main effects and interactions in the model remained unchanged. Expected benefit was more influential in respondents' decision making than expected side effects. The absence of interaction effects suggests that respondents consider the side effects and benefits independently.The concomitant mechanical deformation and solidification of melts are relevant to a broad range of phenomena. Examples include the preparation of cotton candy, the atomization of metals, the manufacture of glass fibers, and the formation of elongated structures in volcanic eruptions known as Pele's hair. Usually, solid-like deformations during solidification are neglected as the melt is much more malleable in its initial liquid-like form. Here we demonstrate how elastic deformations in the midst of solidification, i.e., while the melt responds as a very soft solid ([Formula see text] Pa), can lead to the formation of previously unknown periodic structures. Namely, we generate an array of droplets on a thin layer of liquid elastomer melt coated on the outside of a rotating cylinder through the Rayleigh-Taylor instability. Then, as the melt cures and goes through its gelation point, the rotation speed is increased and the drops stretch into hairs. The ongoing solidification eventually hardens the material, permanently "freezing" these elastic deformations into a patterned solid. Using experiments, simulation, and theory, we demonstrate that the formation of our two-step patterns can be rationalized when combining the tools from fluid mechanics, elasticity, and statistics. Our study therefore provides a framework to analyze multistep pattern formation processes and harness them to assemble complex materials.Reconstructing the history of biodiversity has been hindered by often-separate analyses of stem and crown groups of the clades in question that are not easily understood within the same unified evolutionary framework. Here, we investigate the evolutionary history of birds by analyzing three supertrees that combine published phylogenies of both stem and crown birds. Our analyses reveal three distinct large-scale increases in the diversification rate across bird evolutionary history. The first increase, which began between 160 and 170 Ma and reached its peak between 130 and 135 Ma, corresponds to an accelerated morphological evolutionary rate associated with the locomotory systems among early stem birds. This radiation resulted in morphospace occupation that is larger and different from their close dinosaurian relatives, demonstrating the occurrence of a radiation among early stem birds. The second increase, which started ∼90 Ma and reached its peak between 65 and 55 Ma, is associated with rapid evolution of the cranial skeleton among early crown birds, driven differently from the first radiation. The third increase, which occurred after ∼40 to 45 Ma, has yet to be supported by quantitative morphological data but gains some support from the fossil record. Our analyses indicate that the bird biodiversity evolution was influenced mainly by long-term climatic changes and also by major paleobiological events such as the Cretaceous-Paleogene (K-Pg) extinction.
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