Bhattacharjee, Tapomoy; Amchin, Daniel; Alert, Ricard; Ott, Jenna; Datta, Sujit
Abstract:
Collective migration -- the directed, coordinated motion of many self-propelled agents -- is a fascinating emergent behavior exhibited by active matter that has key functional implications for biological systems. Extensive studies have elucidated the different ways in which this phenomenon may arise. Nevertheless, how collective migration can persist when a population is confronted with perturbations, which inevitably arise in complex settings, is poorly understood. Here, by combining experiments and simulations, we describe a mechanism by which collectively migrating populations smooth out large-scale perturbations in their overall morphology, enabling their constituents to continue to migrate together. We focus on the canonical example of chemotactic migration of Escherichia coli, in which fronts of cells move via directed motion, or chemotaxis, in response to a self-generated nutrient gradient. We identify two distinct modes in which chemotaxis influences the morphology of the population: cells in different locations along a front migrate at different velocities due to spatial variations in (i) the local nutrient gradient and in (ii) the ability of cells to sense and respond to the local nutrient gradient. While the first mode is destabilizing, the second mode is stabilizing and dominates, ultimately driving smoothing of the overall population and enabling continued collective migration. This process is autonomous, arising without any external intervention; instead, it is a population-scale consequence of the manner in which individual cells transduce external signals. Our findings thus provide insights to predict, and potentially control, the collective migration and morphology of cell populations and diverse other forms of active matter.
Chen, Xu; Li, Zhongshu; Gallagher, Kevin P.; Mauzerall, Denise L.
Abstract:
Power sector decarbonization requires a fundamental redirection of global finance from fossil fuel infrastructure towards low carbon technologies. Bilateral finance plays an important role in the global energy transition to non-fossil energy, but an understanding of its impact is limited. Here, for the first time, we compare the influence of overseas finance from the three largest economies – United States, China, and Japan – on power generation development beyond their borders and evaluate the associated long-term CO2 emissions. We construct a new dataset of Japanese and U.S. overseas power generation finance between 2000-2018 by analyzing their national development finance institutions’ press releases and annual reports and tracking their foreign direct investment at the power plant level. Synthesizing this new data with previously developed datasets for China, we find that the three countries’ overseas financing concentrated in fossil fuel power technologies over the studied period. Financing commitments from China, Japan, and the United States facilitated 101 GW, 95 GW, and 47 GW overseas power capacity additions, respectively. The majority of facilitated capacity additions are fossil fuel plants (64% for China, 87% for Japan, and 66% for the United States). Each of the countries’ contributions to non-hydro renewable generation was less than 15% of their facilitated capacity additions. Together, we estimate that overseas fossil fuel power financing through 2018 from these three countries will lock in 24 Gt CO2 emissions by 2060. If climate targets are to be met, replacing bilateral fossil fuel financing with financing of renewable technologies is crucial.
Derrida’s Margins <derridas-margins.princeton.edu> is a website and online research tool for annotations from the Library of Jacques Derrida, housed at Princeton University Library (PUL) <library.princeton.edu>. Jacques Derrida is one of the major figures of twentieth-century thought, and his library--which bears the traces of decades of close reading--represents a major intellectual archive. This project focused on annotations related to Derrida’s landmark 1967 work De la grammatologie (Of Grammatology).
Derrida’s Margins <derridas-margins.princeton.edu> is a website and online research tool for annotations from the Library of Jacques Derrida, housed at Princeton University Library (PUL) <library.princeton.edu>. Jacques Derrida is one of the major figures of twentieth-century thought, and his library--which bears the traces of decades of close reading--represents a major intellectual archive. This project focused on annotations related to Derrida’s landmark 1967 work De la grammatologie (Of Grammatology).
Choi, W.; Poli, F. M.; Li, M. H.; Baek, S. G.; Gorelenkova, M.; Ding, B. J.; Gong, X. Z.; Chan, A.; Duan, Y. M.; Hu, J. H.; Lian, H.; Lin, S. Y.; Liu, H. Q.; Qian, J. P.; Wallace, G.; Wang, Y. M.; Zang, Q.; Zhao, H. L.
The dielectric function for "Astrodust" grain material is provided for different assumed values of the dust grain shape (spheroid axis ratio) and porosity (vacuum fraction), and fraction of the interstellar iron present as metallic inclusions. For each case, the dielectric function is obtained by requiring that the grains reproduce the observed infrared opacity, and match to a physically reasonable dielectric function at 1 micron, and extending to X-ray energies. The derived dielectric functions satisfy the Kramers-Kronig relations. Dielectric functions are provided from 1 Angstrom to 5 cm (12.4 keV to 2.59e-5 eV).
For each dielectric function, we also calculate absorption and scattering corss sections for spheroidal grains, for three orientations of the grain relative to incident linearly-polarized light, for wavelengths from the Lyman limit (0.0912 micron) to the microwave (4 cm), and grain "effective radii" a_eff from 3.162A to 5.012 micron.
These data include 39 structured interview transcripts. Each case is someone who worked at the time for Uber, UberEats, Lyft, and/or Amazon Flex (Amazon’s contractor delivery service). These data were collected between July and September 2019. All but one of the interviews occurred over the phone. My questions are focused on the structure of their gig work jobs and the technology they used at work or expected to use at work in the future. I included a description of the data, the recruitment methods, and the discussion guide in this ReadMe file.