Axiomatic Districting

In a framework with two parties, deterministic voter preferences and a type of geographical constraints, we propose a set of simple axioms and show that they jointly characterize the districting rule that maximizes the number of districts one party can win, given the distribution of individual votes (the \optimal gerrymandering rule"). As a corollary, we obtain that no districting rule can satisfy our axioms and treat parties symmetrically

What’s a Federalist to Do? The Impending Clash Between Textualism and Federalism in State Congressional Redistricting Suits Under Article 1, Section 4

Nanofluids (NFs) are nanotechnology-based colloidal dispersion prepared by dispersing nanoparticles (NPs) in conventional liquids, as the base liquid. These advanced fluids have displayed potential to enhance the performance of conventional heat transfer fluids. This work aims at providing an insight to the field of NFs by investigating in detail the fabrication and evaluation of physico-chemical, thermo-physical and heat transfer characteristics of NFs for practical heat transfer applications. However, in order to utilize NFs as heat transfer fluids in real applications there are some challenges to overcome. Therefore, our goal is not only to optimize the thermo-physical properties of NFs with the highest thermal conductivity (TC) and minimal impact of NPs on viscosity, but also on preparing NFs with good stability and the best heat transfer performance. In the first stage, detailed studies were carried out to engineer NFs with good stability and optimal thermo-physical properties. In this work we investigated the most important factors, and the dependence of thermo-physical properties of NFs, including NP composition and concentration, NF stability, surface modifiers, particle size (NP size and particle with micron size), NF preparation method (two-step vs one-step method) and base liquid was studied. We also demonstrated, for the first time, the role of crystal structure, exemplified by alpha- and beta- SiC particles, on thermo-physical properties of NFs. For these purposes several NFs were fabricated using different nanostructured materials and various base liquids by one-step and two-step methods. An optimization procedure was designed to keep a suitable control in order to reach the ultimate aim where several stages were involved to check the desired characteristics of each NF system. Among several NFs systems studied in the first stage evaluation, a particular NF system with 9 wt% concentration, engineered by dispersing SiC NPs with alpha- crystal structure in water/ethylene glycol as based liquid exhibited the optimal thermo-physical properties. This NF was the only case which could pass the all criteria involved in the optimization procedure by exhibiting good stability, TC enhancements of ~20% with only 14% increase in viscosity at 20 oC. Therefore, this engineered NF was considered for next phase evaluation, where heat transfer coefficient (HTC) tests were designed and carried out to evaluate the thermal transport property of the selected alpha- SiC NF. A HTC enhancement of 5.5% at equal pumping power, as realistic comparison criteria, was obtained indicating the capability of this kind of NFs to be used in industrial heat transfer applications. These findings are among the few studies in the literature where the heat transfer characteristics of the NFs were noticeable, reproducible and based on a realistic situation with capability of commercializing as effective heat transfer fluid.  QC 20140416Nanohe

Votemandering: Strategies and Fairness in Political Redistricting

Gerrymandering, the deliberate manipulation of electoral district boundaries for political advantage, is a persistent issue in U.S. redistricting cycles. This paper introduces and analyzes a new phenomenon, 'votemandering'- a strategic blend of gerrymandering and targeted political campaigning, devised to gain more seats by circumventing fairness measures. It leverages accurate demographic and socio-political data to influence voter decisions, bolstered by advancements in technology and data analytics, and executes better-informed redistricting. Votemandering is established as a Mixed Integer Program (MIP) that performs fairness-constrained gerrymandering over multiple election rounds, via unit-specific variables for campaigns. To combat votemandering, we present a computationally efficient heuristic for creating and testing district maps that more robustly preserve voter preferences. We analyze the influence of various redistricting constraints and parameters on votemandering efficacy. We explore the interconnectedness of gerrymandering, substantial campaign budgets, and strategic campaigning, illustrating their collective potential to generate biased electoral maps. A Wisconsin State Senate redistricting case study substantiates our findings on real data, demonstrating how major parties can secure additional seats through votemandering. Our findings underscore the practical implications of these manipulations, stressing the need for informed policy and regulation to safeguard democratic processes

A Graph Partitioning Model of Congressional Redistricting

Redrawing congressional districts in the United States is a constitutionally required, yet politically controversial, task undertaken after each decennial census. Federal law requires contiguous, `relatively compact\u27 congressional districts that maintain `approximately equal\u27 population. Controversy is introduced when individual states redraw their districts, or redistrict, using partisan committees. States such as Ohio continue to redistrict with a committee appointed according to the current proportion of legislators\u27 political parties to the whole. When political parties have majority power in redistricting committees, they can draw districts in a way that gives their party the best chance to keep its majority representation, a process called gerrymandering. Mathematical redistricting models seek an unbiased computational approach to the problem. Rather than trust partisan committees, mathematical modeling approaches rely upon well-defined methods in computational geometry, graph theory, game theory, and other fields. Here, we discuss two such approaches. The first, given as a background for comparison, constructs Voronoi diagrams to redistrict states into convex polygons, which are generally considered `compact\u27. We give greater emphasis to a new model that discretizes a state\u27s population and partitions it into regions of approximately equal population. This model, our main focus, relies upon graph partitioning to achieve the desired result and uses census population data as the sole parameter in redistricting