University of Amsterdam

About: University of Amsterdam is a education organization based out in Amsterdam, Noord-Holland, Netherlands. It is known for research contribution in the topics: Population & Randomized controlled trial. The organization has 59309 authors who have published 140894 publications receiving 5984137 citations. The organization is also known as: UvA & Universiteit van Amsterdam.

Making sense of financialization

Abstract: Since the early 2000s, scholars from a variety of disciplines have used the concept of financialization to describe a host of structural changes in the advanced political economies. Studies of financialization interrogate how an increasingly autonomous realm of global finance has altered the underlying logics of the industrial economy and the inner workings of democratic society. This paper evaluates the insights of more than a decade of scholarship on financialization. Three approaches will be discussed: the emergence of a new regime of accumulation, the ascendency of the shareholder value orientation and the financialization of everyday life. It is argued that a deeper understanding of financialization will lead to a better understanding of organized interests, the politics of the welfare state, and processes of institutional change.

Surviving sepsis campaign: international guidelines for management of sepsis and septic shock 2021.

Abstract: Background Sepsis poses a global threat to millions of lives. The Surviving Sepsis Campaign (SSC) guidelines provide evidence-based recommendations on the recognition and management of sepsis and its complications. Methods We formed a panel of 60 experts from 22 countries and 11 members of the public. The panel prioritized questions that are relevant to the recognition and management of sepsis and septic shock in adults. New questions and sections were addressed, relative to the previous guidelines. These questions were grouped under 6 subgroups (screening and early treatment, infection, hemodynamics, ventilation, additional therapies, and long-term outcomes and goals of care). With input from the panel and methodologists, professional medical librarians performed the search strategy tailored to either specific questions or a group of relevant questions. A dedicated systematic review team performed screening and data abstraction when indicated. For each question, the methodologists, with input from panel members, summarized the evidence assessed and graded the quality of evidence using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach. The panel generated recommendations using the evidence-to-decision framework. Recommendations were either strong or weak, or in the form of best practice statements. When evidence was insufficient to support a recommendation, the panel was surveyed to generate “in our practice” statements. Results The SSC panel issued 93 statements: 15 best practice statements, 15 strong recommendations, and 54 weak recommendations and no recommendation was provided for 9 questions. The recommendations address several important clinical areas related to screening tools, acute resuscitation strategies, management of fluids and vasoactive agents, antimicrobials and diagnostic tests and the use of additional therapies, ventilation management, goals of care, and post sepsis care. Conclusion The SSC panel issued evidence-based recommendations to help support key stakeholders caring for adults with sepsis or septic shock and their families.

Heterogeneous Agent Models in Economics and Finance

Abstract: This chapter surveys work on dynamic heterogeneous agent models (HAMs) in economics and finance. Emphasis is given to simple models that, at least to some extent, are tractable by analytic methods in combination with computational tools. Most of these models are behavioral models with boundedly rational agents using different heuristics or rule of thumb strategies that may not be perfect, but perform reasonably well. Typically these models are highly nonlinear, e.g. due to evolutionary switching between strategies, and exhibit a wide range of dynamical behavior ranging from a unique stable steady state to complex, chaotic dynamics. Aggregation of simple interactions at the micro level may generate sophisticated structure at the macro level. Simple HAMs can explain important observed stylized facts in financial time series, such as excess volatility, high trading volume, temporary bubbles and trend following, sudden crashes and mean reversion, clustered volatility and fat tails in the returns distribution.