No abstract

This Article contributes to the growing literature on the influence of index funds on corporate governance by providing new data on index funds' ownership, voting control, and impact on shareholder proposal outcomes. The Article first presents data on the firm ownership and voting control of the three largest index funds (the Big Three) at Fortune 250 companies. It finds that the Big Three combined are the largest shareholder in 96% of Fortune 250 companies, that Vanguard and BlackRock combined (the Big Two) are the largest shareholder in 94.4% of such companies, and that Vanguard alone (the Big One) is the largest shareholder in 65.6% of such companies. The Article next analyzes the power of the Big Three index funds to decide the outcome of shareholder proposals. It presents data on the voting margins for all shareholder proposals at Fortune 250 companies in calendar years 2018 and 2019. It then pairs the voting-margin data with the voting-control data to provide a market-wide picture of which shareholder proposals are likely within the Big Three's influence. The findings suggest that the Big Three already possess sufficient voting power to determine the outcome of a majority of shareholder proposals. Additionally, the Article provides data on the Big Three's influence over specific categories of shareholder proposals. It finds that the Big Three have the power to determine approximately 50% of the environmental and social proposals (with low error rates) and approximately 65% of governance proposals (with somewhat higher error rates). In light of these findings, the Article explores the profound implications of this proxy voting power and proposes methods for investors to reclaim their autonomy.

No abstract

No abstract

Single-molecule localization microscopy (SMLM) is a developing field of biological imaging that employs the use of photoswitching fluorophores to image sub-cellular biological structures at a higher resolution than was previously possible. These fluorophores are used for protein labeling, so that the sample can be imaged under fluorescence microscopy. This type of microscopy requires the use of many different types of fluorophores, which are fluorescent organic compounds that blink stochastically on and off. Thus, it is critical for developers in the field to have easy access to statistical models of the behaviors of different fluorophores. Here, we take AlexaFluor 647 and analyze it using a fluorescence microscope, taking data on its blinking behaviors and discerning its properties when immersed in a fluorescence-dampening buffer solution. We find that the compound behaves best in buffer solution, and we forge a new methodology for evaluating new fluorophores in a systematic fashion using readily available computer software.