Marcher Hinson (museumdrill9)

Electronic consult (eConsult) systems allow specialists more flexibility to respond to referrals more efficiently, thereby increasing access in under-resourced healthcare settings like safety net systems. Understanding the usage patterns of eConsult system is an important part of improving specialist efficiency. In this work, we develop and apply classifiers to a dataset of eConsult questions from primary care providers to specialists, classifying the messages for how they were triaged by the specialist office, and the underlying type of clinical question posed by the primary care provider. We show that pre-trained transformer models are strong baselines, with improving performance from domain-specific training and shared representations.Big data can easily be contaminated by outliers or contain variables with heavy-tailed distributions, which makes many conventional methods inadequate. To address this challenge, we propose the adaptive Huber regression for robust estimation and inference. The key observation is that the robustification parameter should adapt to the sample size, dimension and moments for optimal tradeoff between bias and robustness. Our theoretical framework deals with heavy-tailed distributions with bounded (1 + δ)-th moment for any δ > 0. Daidzein solubility dmso We establish a sharp phase transition for robust estimation of regression parameters in both low and high dimensions when δ ≥ 1, the estimator admits a sub-Gaussian-type deviation bound without sub-Gaussian assumptions on the data, while only a slower rate is available in the regime 0 less then δ less then 1 and the transition is smooth and optimal. In addition, we extend the methodology to allow both heavy-tailed predictors and observation noise. Simulation studies lend further support to the theory. In a genetic study of cancer cell lines that exhibit heavy-tailedness, the proposed methods are shown to be more robust and predictive.International business (IB) research is designed to explore and explain the inherent complexity of international business, which arises from the multiplicity of entities, multiplexity of interactions, and dynamism of the global economic system. To analyze this complexity, IB scholars have developed four research lenses difference, distance, diversity, and disparity. These four lenses on complexity have created not only unique research opportunities for IB scholarship but also unique research methodological challenges. We therefore view complexity as the underlying cause of the unique methodological challenges facing international business research. We offer several recommendations to help IB scholars embrace this complexity and conduct reliable, interesting, and practically relevant research.The COVID-19 pandemic radically and rapidly changed the world, including the world of business economists. Eight NABE members employed in a wide variety of fields discuss how their lives and work were transformed.The Mineral Raw Materials Industry was hit severely by COVID-19. Declines in production and collapsing demands characterize the year 2020. The EU Commission's proposal to raise the 2030 greenhouse gas emission reduction targets, including emissions and removals from 40 to at least 55%, poses a challenge for the European industry, especially the energy-intensive one. The European Commission's idea for a carbon border tax adjustment mechanism and sustainable finance models (sustainable finance and taxonomy) are currently the subject of controversial debate. Economic burdens on specific branches and the industrial site have to be taken into account, if a carbon leakage scenario is to be avoided and if Europe has to be given a fair chance to stay competitive in spite of an ambitious climate policy. It is important, not only to protect climate and environment, but also the European industry, jobs and social system. The transformation towards a sustainable economy and society necessitates an increasing demand of mineral ra