11,086 research outputs found
On the NP-Hardness of Approximating Ordering Constraint Satisfaction Problems
We show improved NP-hardness of approximating Ordering Constraint
Satisfaction Problems (OCSPs). For the two most well-studied OCSPs, Maximum
Acyclic Subgraph and Maximum Betweenness, we prove inapproximability of
and .
An OCSP is said to be approximation resistant if it is hard to approximate
better than taking a uniformly random ordering. We prove that the Maximum
Non-Betweenness Problem is approximation resistant and that there are width-
approximation-resistant OCSPs accepting only a fraction of
assignments. These results provide the first examples of
approximation-resistant OCSPs subject only to P \NP
Mesomorphic properties of alkoxybenzylidene- aminoacetophenones
Liquid crystal phase transitions in compounds of alkoxybenzylidene-aminoacetophene serie
Tripartite to Bipartite Entanglement Transformations and Polynomial Identity Testing
We consider the problem of deciding if a given three-party entangled pure
state can be converted, with a non-zero success probability, into a given
two-party pure state through local quantum operations and classical
communication. We show that this question is equivalent to the well-known
computational problem of deciding if a multivariate polynomial is identically
zero. Efficient randomized algorithms developed to study the latter can thus be
applied to the question of tripartite to bipartite entanglement
transformations
A Hypergraph Dictatorship Test with Perfect Completeness
A hypergraph dictatorship test is first introduced by Samorodnitsky and
Trevisan and serves as a key component in their unique games based \PCP
construction. Such a test has oracle access to a collection of functions and
determines whether all the functions are the same dictatorship, or all their
low degree influences are Their test makes queries and has
amortized query complexity but has an inherent loss of
perfect completeness. In this paper we give an adaptive hypergraph dictatorship
test that achieves both perfect completeness and amortized query complexity
.Comment: Some minor correction
Improved Approximation Algorithms for Projection Games
The projection games (aka Label-Cover) problem is of great importance to the field of approximation algorithms, since most of the NP-hardness of approximation results we know today are reductions from Label-Cover. In this paper we design several approximation algorithms for projection games:
1. A polynomial-time approximation algorithm that improves on the previous best approximation by Charikar, Hajiaghayi and Karloff [7].
2. A sub-exponential time algorithm with much tighter approximation for the case of smooth projection games.
3. A PTAS for planar graphs.National Science Foundation (U.S.) (Grant 1218547
Predictors of dental visits among primary school children in the rural Australian community of Lithgow
Background: Regular dental attendance is significant in maintaining and improving children’s oral health and well-being. This study aims to determine the factors that predict and influence dental visits in primary school children residing in the rural community of Lithgow, New South Wales (NSW), Australia. Methods: All six primary schools of Lithgow were approached to participate in a cross-sectional survey prior to implementing water fluoridation in 2014. Children aged 6–13 years (n = 667) were clinically examined for their oral health status and parents were requested to complete a questionnaire on fluoride history, diet, last dental visit, and socio-demographic characteristics. Multiple logistic regression analyses were employed to examine the independent predictors of a 6-monthly and a yearly dental visit. Results: Overall, 53% of children visited a dentist within six months and 77% within twelve months. In multiple logistic regression analyses, age of the child and private health insurance coverage were significantly associated with both 6-monthly and twelve-month dental visits. In addition, each serve of chocolate consumption was significantly associated with a 27% higher odds (OR = 1.27, 95% CI: 1.05-1.54) of a 6-monthly dental visit. Conclusion: It is imperative that the socio-demographic and dietary factors that influence child oral health must be effectively addressed when developing the oral health promotion policies to ensure better oral health outcomes.James Rufus John, Haider Mannan, Subrat Nargundkar, Mario D’Souza, Loc Giang Do and Amit Aror
Credimus
We believe that economic design and computational complexity---while already
important to each other---should become even more important to each other with
each passing year. But for that to happen, experts in on the one hand such
areas as social choice, economics, and political science and on the other hand
computational complexity will have to better understand each other's
worldviews.
This article, written by two complexity theorists who also work in
computational social choice theory, focuses on one direction of that process by
presenting a brief overview of how most computational complexity theorists view
the world. Although our immediate motivation is to make the lens through which
complexity theorists see the world be better understood by those in the social
sciences, we also feel that even within computer science it is very important
for nontheoreticians to understand how theoreticians think, just as it is
equally important within computer science for theoreticians to understand how
nontheoreticians think
The Traveling Salesman Problem: Low-Dimensionality Implies a Polynomial Time Approximation Scheme
The Traveling Salesman Problem (TSP) is among the most famous NP-hard
optimization problems. We design for this problem a randomized polynomial-time
algorithm that computes a (1+eps)-approximation to the optimal tour, for any
fixed eps>0, in TSP instances that form an arbitrary metric space with bounded
intrinsic dimension.
The celebrated results of Arora (A-98) and Mitchell (M-99) prove that the
above result holds in the special case of TSP in a fixed-dimensional Euclidean
space. Thus, our algorithm demonstrates that the algorithmic tractability of
metric TSP depends on the dimensionality of the space and not on its specific
geometry. This result resolves a problem that has been open since the
quasi-polynomial time algorithm of Talwar (T-04)
Impact of a brief faculty training to improve patient-centered communication while using electronic health records
Objective
Despite rapid EHR adoption, few faculty receive training in how to implement patient-centered communication skills while using computers in exam rooms. We piloted a patient-centered EHR use training to address this issue.
Methods
Faculty received four hours of training at Cleveland Clinic and a condensed 90-minute version at the University of Chicago. Both included a lecture and a Group-Objective Structured Clinical Exam (GOSCE) experience. Direct observations of 10 faculty in their clinical practices were performed pre- and post-workshop.
Results
Thirty participants (94%) completed a post-workshop evaluation assessing knowledge, attitude, and skills. Faculty reported that training was important, relevant, and should be required for all providers; no differences were found between longer versus shorter training. Participants in the longer training reported higher GOSCE efficacy, however shorter workshop participants agreed more with the statement that they had gained new knowledge. Faculty improved their patient-centered EHR use skills in clinical practice on post- versus pre-workshop ratings using a validated direct-observation rating tool.
Conclusion
A brief lecture and GOSCE can be effective in training busy faculty on patient-centered EHR use skills.
Practice Implications
Faculty training on patient-centered EHR skills can enhance patient-doctor communication and promotes positive role modeling of these skills to learners
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