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Democratizing electoral geography: Visualizing votes and political neogeography
The association between county political inclination and obesity: Results from the 2012 presidential election in the United States.
ObjectiveWe examined whether stable, county-level, voter preferences were significantly associated with county-level obesity prevalence using data from the 2012 US Presidential election. County voting preference for the 2012 Republican Party presidential candidate was used as a proxy for voter endorsement of personal responsibility approaches to reducing population obesity risk versus approaches featuring government-sponsored, multi-sectoral efforts like those recommended by the Centers for Disease Control Centers for Disease Control (CDC, 2009).MethodCartographic visualization and spatial analysis were used to evaluate the geographic clustering of obesity prevalence rates by county, and county-level support for the Republican Party candidate in the 2012 U.S. presidential election. The spatial analysis informed the spatial econometric approach employed to model the relationship between political preferences and other covariates with obesity prevalence.ResultsAfter controlling for poverty rate, percent African American and Latino populations, educational attainment, and spatial autocorrelation in the error term, we found that higher county-level obesity prevalence rates were associated with higher levels of support for the 2012 Republican Party presidential candidate.ConclusionFuture public health efforts to understand and reduce obesity risk may benefit from increased surveillance of this and similar linkages between political preferences and health risks
Belief Propagation for Linear Programming
Belief Propagation (BP) is a popular, distributed heuristic for performing
MAP computations in Graphical Models. BP can be interpreted, from a variational
perspective, as minimizing the Bethe Free Energy (BFE). BP can also be used to
solve a special class of Linear Programming (LP) problems. For this class of
problems, MAP inference can be stated as an integer LP with an LP relaxation
that coincides with minimization of the BFE at ``zero temperature". We
generalize these prior results and establish a tight characterization of the LP
problems that can be formulated as an equivalent LP relaxation of MAP
inference. Moreover, we suggest an efficient, iterative annealing BP algorithm
for solving this broader class of LP problems. We demonstrate the algorithm's
performance on a set of weighted matching problems by using it as a cutting
plane method to solve a sequence of LPs tightened by adding ``blossom''
inequalities.Comment: To appear in ISIT 201
DDMF: An Efficient Decision Diagram Structure for Design Verification of Quantum Circuits under a Practical Restriction
Recently much attention has been paid to quantum circuit design to prepare
for the future "quantum computation era." Like the conventional logic
synthesis, it should be important to verify and analyze the functionalities of
generated quantum circuits. For that purpose, we propose an efficient
verification method for quantum circuits under a practical restriction. Thanks
to the restriction, we can introduce an efficient verification scheme based on
decision diagrams called
Decision Diagrams for Matrix Functions (DDMFs). Then, we show analytically
the advantages of our approach based on DDMFs over the previous verification
techniques. In order to introduce DDMFs, we also introduce new concepts,
quantum functions and matrix functions, which may also be interesting and
useful on their own for designing quantum circuits.Comment: 15 pages, 14 figures, to appear IEICE Trans. Fundamentals, Vol.
E91-A, No.1
Minimum Weight Perfect Matching via Blossom Belief Propagation
Max-product Belief Propagation (BP) is a popular message-passing algorithm
for computing a Maximum-A-Posteriori (MAP) assignment over a distribution
represented by a Graphical Model (GM). It has been shown that BP can solve a
number of combinatorial optimization problems including minimum weight
matching, shortest path, network flow and vertex cover under the following
common assumption: the respective Linear Programming (LP) relaxation is tight,
i.e., no integrality gap is present. However, when LP shows an integrality gap,
no model has been known which can be solved systematically via sequential
applications of BP. In this paper, we develop the first such algorithm, coined
Blossom-BP, for solving the minimum weight matching problem over arbitrary
graphs. Each step of the sequential algorithm requires applying BP over a
modified graph constructed by contractions and expansions of blossoms, i.e.,
odd sets of vertices. Our scheme guarantees termination in O(n^2) of BP runs,
where n is the number of vertices in the original graph. In essence, the
Blossom-BP offers a distributed version of the celebrated Edmonds' Blossom
algorithm by jumping at once over many sub-steps with a single BP. Moreover,
our result provides an interpretation of the Edmonds' algorithm as a sequence
of LPs
The Super Size of America: An Economic Estimation of Body Mass Index and Obesity in Adults
The increased prevalence of obesity in the US stresses the need for answers as to why this rapid rise has occurred. This paper employs micro-level data from the First, Second, and Third National Health and Nutrition xamination Surveys to determine the effects that state-level policies have on BMI and obesity. These policies, which include restaurants per capita, the gasoline tax, the cigarette tax, and clean indoor air laws, display many of the expected effects on obesity and explain a substantial amount of its trend. We control for individual-level measures of household income, years of formal schooling completed, and marital status.
The Super Size of America: An Economic Estimation of Body Mass Index and Obesity in Adults
The increased prevalence of obesity in the United States stresses the pressing need for answers as to why this rapid rise has occurred. This paper employs micro-level data from the First, Second, and Third National Health and Nutrition Examination Surveys to determine the effects that various state-level variables have on body mass index and obesity. These variables, which include the per capita number of restaurants, the gasoline tax, the cigarette tax, and clean indoor air laws, display many of the expected effects on obesity and explain a substantial amount of its trend. These findings control for individual-level measures of household income, years of formal schooling completed, and marital status.
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