2,478 research outputs found
Hamming Approximation of NP Witnesses
Given a satisfiable 3-SAT formula, how hard is it to find an assignment to
the variables that has Hamming distance at most n/2 to a satisfying assignment?
More generally, consider any polynomial-time verifier for any NP-complete
language. A d(n)-Hamming-approximation algorithm for the verifier is one that,
given any member x of the language, outputs in polynomial time a string a with
Hamming distance at most d(n) to some witness w, where (x,w) is accepted by the
verifier. Previous results have shown that, if P != NP, then every NP-complete
language has a verifier for which there is no
(n/2-n^(2/3+d))-Hamming-approximation algorithm, for various constants d > 0.
Our main result is that, if P != NP, then every paddable NP-complete language
has a verifier that admits no (n/2+O(sqrt(n log n)))-Hamming-approximation
algorithm. That is, one cannot get even half the bits right. We also consider
natural verifiers for various well-known NP-complete problems. They do have
n/2-Hamming-approximation algorithms, but, if P != NP, have no
(n/2-n^epsilon)-Hamming-approximation algorithms for any constant epsilon > 0.
We show similar results for randomized algorithms
What Are They Saying About the Jonah Psalm? An Analysis of the Current Trends in its Interpretation
The aim of this thesis is to examine the current state of the question of the Jonah psalm, particularly its peculiar placement within the prose of the book of Jonah. Its date of composition, rhetorical features, and overall purpose are of specific interest, and are inspected as such. Definitive answers prove elusive in regards to the psalm’s date of composition, as it can be placed, with varying degrees of conviction, between the 8th and 2nd centuries BC. Rhetorical analysis proves more enlightening, as comparing the psalm to the surrounding prose underscores the linguistic and rhetorical synergy between the two, however vague. The overall purpose of the psalm’s placement within the prose produces a number of hypotheses, the most curious of which is the idea that the entire book is a satire of the Old Testament prophetic archetype, and the psalm is used to elucidate the parodic aspects of the story as a whole, perhaps for the purpose of both excoriating and educating those who would be quick to condemn others born outside of the Covenant
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Health benefits and control costs of tightening particulate matter emissions standards for coal power plants - The case of Northeast Brazil.
Exposure to ambient particulate matter (PM) caused an estimated 4.2 million deaths worldwide in 2015. However, PM emission standards for power plants vary widely. To explore if the current levels of these standards are sufficiently stringent in a simple cost-benefit framework, we compared the health benefits (avoided monetized health costs) with the control costs of tightening PM emission standards for coal-fired power plants in Northeast (NE) Brazil, where ambient PM concentrations are below World Health Organization (WHO) guidelines. We considered three Brazilian PM10 (PMx refers to PM with a diameter under x micrometers) emission standards and a stricter U.S. EPA standard for recent power plants. Our integrated methodology simulates hourly electricity grid dispatch from utility-scale power plants, disperses the resulting PM2.5, and estimates selected human health impacts from PM2.5 exposure using the latest integrated exposure-response model. Since the emissions inventories required to model secondary PM are not available in our study area, we modeled only primary PM so our benefit estimates are conservative. We found that tightening existing PM10 emission standards yields health benefits that are over 60 times greater than emissions control costs in all the scenarios we considered. The monetary value of avoided hospital admissions alone is at least four times as large as the corresponding control costs. These results provide strong arguments for considering tightening PM emission standards for coal-fired power plants worldwide, including in regions that meet WHO guidelines and in developing countries
Advances in semantic representation for multiscale biosimulation: a case study in merging models
As a case-study of biosimulation model integration, we describe our experiences applying the SemSim methodology to integrate independently-developed, multiscale models of cardiac circulation. In particular, we have integrated the CircAdapt model (written by T. Arts for MATLAB) of an adapting vascular segment with a cardiovascular system model (written by M. Neal for JSim). We report on three results from the model integration experience. First, models should be explicit about simulations that occur on different time scales. Second, data structures and naming conventions used to represent model variables may not translate across simulation languages. Finally, identifying the dependencies among model variables is a non-trivial task. We claim that these challenges will appear whenever researchers attempt to integrate models from others, especially when those models are written in a procedural style (using MATLAB, Fortran, etc.) rather than a declarative format (as supported by languages like SBML, CellML or JSim’s MML)
Integration of multi-scale biosimulation models via light-weight semantics
Currently, biosimulation researchers use a variety of computational environments and languages to model biological processes. Ideally, researchers should be able to semi- automatically merge models to more effectively build larger, multi-scale models. How- ever, current modeling methods do not capture the underlying semantics of these models sufficiently to support this type of model construction. In this paper, we both propose a general approach to solve this problem, and we provide a specific example that demon- strates the benefits of our methodology. In particular, we describe three biosimulation models: (1) a cardio-vascular fluid dynamics model, (2) a model of heart rate regulation via baroreceptor control, and (3) a sub-cellular-level model of the arteriolar smooth mus- cle. Within a light-weight ontological framework, we leverage reference ontologies to match concepts across models. The light-weight ontology then helps us combine our three models into a merged model that can answer questions beyond the scope of any single model
How Higher Mortgage Interest Rates Can Widen Racial Gaps in Housing Wealth: The Case of Newark, New Jersey
Trends in macroeconomic conditions and policy have helped to boost longer-term interest rates, including mortgage rates, over the past year. This has important implications for the wealth gap between white and Black or Hispanic households. The standard narrative is that higher interest rates, especially when combined with higher house prices and lower incomes, reduce homebuying affordability for Black and Hispanic households relative to white households. And this, in turn, implies that these households of color will find that achieving homeownership has become more difficult, thereby widening the racial wealth gap. This report illustrates that under a higher mortgage rate regime, the pace of principal reduction is slower over most of the life of a 30-year fixed-rate mortgage. Using data covering purchase loans on one-to-four family mortgages across the city of Newark, NJ, we also show that Black and Hispanic households buying in Newark obtain higher mortgage rates relative to their white peers and therefore pay more in interest for a slower principal reduction. In response, we suggest that more local policymakers assess the benefits of interest-rate buy-downs to improve affordability, close racial wealth gaps in housing, and better insulate historically marginalized communities from macroeconomic shocks
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