Turbulent Heat Transfer in Non-Newtonian Fluids

The heat transfer coefficients of the turbulent flow of not only pseudoplastic, but dilatant and also Bingham fluids in a rectangular duct and in a circular tube were measured experimentally, and correlated by the same characteristic idea with a modified Chilton-Colburn analogy. The equations of heat transfer coefficients thus derived were shown to represent the data well. Moreover, the temperature and velocity profiles in the rectangular duct were measured to compute the eddy diffusivities for momentum and for heat in Newtonian and non-Newtonian fluids, and the correlations of the eddy diffusivities were presented

Heat Transfer to Laminar Flow of Pseudoplastic Fluids

The temperature dependence of viscosity was taken into account in solving the equations of change for laminar flows of pseudoplastic fluids in circular tubes. The solutions were obtained for the entrance and the thermally well developed regions at the conditon of constant heat flux. Those analytical solutions were approximated with the equations of non dimensional moduli, which were in good agreement with the experimental results of the authors. Furthermore, even if the temperature dependence of viscosity was taken into account, the plots of Nusselt numbers at the thermally fully developed region against uₘₐₓ/uₘ were shown to be just shifted on the same curve for those plots of nearly isothermal flow

The Still Secret Ballot: The Limited Privacy Cost of Transparent Election Results

After an election, should election officials release an electronic record of each ballot? The release of such cast vote records could bolster the legitimacy of the certified result. But it may also facilitate vote revelation, where an analyst unravels the secret ballot by uniquely linking vote choices on the anonymous ballot to the voter's name and address in the public voter file. We provide the first empirical study of the extent of vote revelation under several possible election-reporting regimes, ranging from precinct-level results to the individual ballot records known as cast vote records. Using Maricopa County, Arizona, as a case study, we find that cast vote records could reveal less than 0.2% of any voters' choices in the 2020 general election. Perhaps counterintuitively, releasing cast vote records coded by precinct and vote method are no more revelatory than releasing aggregate vote tallies for each precinct and vote method. We conclude that cast vote records are sufficiently privacy-protecting, and suggest how the privacy violations that do remain could be reduced.Comment: Initial draft, 42 pages, 6 figures, 2 table

Evaluating Bias and Noise Induced by the U.S. Census Bureau's Privacy Protection Methods

The United States Census Bureau faces a difficult trade-off between the accuracy of Census statistics and the protection of individual information. We conduct the first independent evaluation of bias and noise induced by the Bureau's two main disclosure avoidance systems: the TopDown algorithm employed for the 2020 Census and the swapping algorithm implemented for the 1990, 2000, and 2010 Censuses. Our evaluation leverages the recent release of the Noisy Measure File (NMF) as well as the availability of two independent runs of the TopDown algorithm applied to the 2010 decennial Census. We find that the NMF contains too much noise to be directly useful alone, especially for Hispanic and multiracial populations. TopDown's post-processing dramatically reduces the NMF noise and produces similarly accurate data to swapping in terms of bias and noise. These patterns hold across census geographies with varying population sizes and racial diversity. While the estimated errors for both TopDown and swapping are generally no larger than other sources of Census error, they can be relatively substantial for geographies with small total populations.Comment: 21 pages, 6 figure

Widespread Partisan Gerrymandering Mostly Cancels Nationally, but Reduces Electoral Competition

Congressional district lines in many U.S. states are drawn by partisan actors, raising concerns about gerrymandering. To separate the partisan effects of redistricting from the effects of other factors including geography and redistricting rules, we compare possible party compositions of the U.S. House under the enacted plan to those under a set of alternative simulated plans that serve as a non-partisan baseline. We find that partisan gerrymandering is widespread in the 2020 redistricting cycle, but most of the electoral bias it creates cancels at the national level, giving Republicans two additional seats on average. Geography and redistricting rules separately contribute a moderate pro-Republican bias. Finally, we find that partisan gerrymandering reduces electoral competition and makes the partisan composition of the U.S. House less responsive to shifts in the national vote.Comment: 10 pages, 4 figures, plus references and appendi

Comment: The Essential Role of Policy Evaluation for the 2020 Census Disclosure Avoidance System

In "Differential Perspectives: Epistemic Disconnects Surrounding the US Census Bureau's Use of Differential Privacy," boyd and Sarathy argue that empirical evaluations of the Census Disclosure Avoidance System (DAS), including our published analysis, failed to recognize how the benchmark data against which the 2020 DAS was evaluated is never a ground truth of population counts. In this commentary, we explain why policy evaluation, which was the main goal of our analysis, is still meaningful without access to a perfect ground truth. We also point out that our evaluation leveraged features specific to the decennial Census and redistricting data, such as block-level population invariance under swapping and voter file racial identification, better approximating a comparison with the ground truth. Lastly, we show that accurate statistical predictions of individual race based on the Bayesian Improved Surname Geocoding, while not a violation of differential privacy, substantially increases the disclosure risk of private information the Census Bureau sought to protect. We conclude by arguing that policy makers must confront a key trade-off between data utility and privacy protection, and an epistemic disconnect alone is insufficient to explain disagreements between policy choices.Comment: Version accepted to Harvard Data Science Revie

Kristeva’s Secret Sartrism: On Revolt in the Postmodern Era

International audienc

他人に対する恐怖の哲学: ジャン＝ポール・サルトルと「私」の傷つきやすさ

National audienc