2,229 research outputs found
Valuation equilibrium
We introduce a new solution concept for games in extensive form with perfect information, valuation equilibrium, which is based on a partition of each player's moves into similarity classes. A valuation of a player'is a real-valued function on the set of her similarity classes. In this equilibrium each player's strategy is optimal in the sense that at each of her nodes, a player chooses a move that belongs to a class with maximum valuation. The valuation of each player is consistent with the strategy profile in the sense that the valuation of a similarity class is the player's expected payoff, given that the path (induced by the strategy profile) intersects the similarity class. The solution concept is applied to decision problems and multi-player extensive form games. It is contrasted with existing solution concepts. The valuation approach is next applied to stopping games, in which non-terminal moves form a single similarity class, and we note that the behaviors obtained echo some biases observed experimentally. Finally, we tentatively suggest a way of endogenizing the similarity partitions in which moves are categorized according to how well they perform relative to the expected equilibrium value, interpreted as the aspiration level
An existence result for a class of nonlinear integral equations of fractional orders
Using a measure of non-compactness argument, we study in this paper the existence of solutions for a class of functional equations involving a fractional integral with respect to another function. Some examples are presented to illustrate the obtained results
The role of airway mucus in pulmonary toxicology.
Airway mucus is a complex airway secretion whose primary function as part of the mucociliary transport mechanism is to to serve as renewable and transportable barrier against inhaled particulates and toxic agents. The rheologic properties necessary for this function are imparted by glycoproteins, or mucins. Some respiratory disease states, e.g., asthma, cystic fibrosis, and bronchitis, are characterized by quantitative and qualitative changes in mucus biosynthesis that contribute to pulmonary pathology. Similar alterations in various aspects of mucin biochemistry and biophysics, leading to mucus hypersecretion and altered mucus rheology, result from inhalation of certain air pollutants, such as ozone, sulfur dioxide, nitrogen dioxide, and cigarette smoke. The consequences of these pollutant-induced alterations in mucus biology are discussed in the context of pulmonary pathophysiology and toxicology
Querying Probabilistic Neighborhoods in Spatial Data Sets Efficiently
In this paper we define the notion
of a probabilistic neighborhood in spatial data: Let a set of points in
, a query point , a distance metric \dist,
and a monotonically decreasing function be
given. Then a point belongs to the probabilistic neighborhood of with respect to with probability f(\dist(p,q)). We envision
applications in facility location, sensor networks, and other scenarios where a
connection between two entities becomes less likely with increasing distance. A
straightforward query algorithm would determine a probabilistic neighborhood in
time by probing each point in .
To answer the query in sublinear time for the planar case, we augment a
quadtree suitably and design a corresponding query algorithm. Our theoretical
analysis shows that -- for certain distributions of planar -- our algorithm
answers a query in time with high probability
(whp). This matches up to a logarithmic factor the cost induced by
quadtree-based algorithms for deterministic queries and is asymptotically
faster than the straightforward approach whenever .
As practical proofs of concept we use two applications, one in the Euclidean
and one in the hyperbolic plane. In particular, our results yield the first
generator for random hyperbolic graphs with arbitrary temperatures in
subquadratic time. Moreover, our experimental data show the usefulness of our
algorithm even if the point distribution is unknown or not uniform: The running
time savings over the pairwise probing approach constitute at least one order
of magnitude already for a modest number of points and queries.Comment: The final publication is available at Springer via
http://dx.doi.org/10.1007/978-3-319-44543-4_3
SrKZnMnAs: a ferromagnetic semiconductor with colossal magnetoresistance
A bulk diluted magnetic semiconductor (Sr,K)(Zn,Mn)As was
synthesized with decoupled charge and spin doping. It has a hexagonal
CaAlSi-type structure with the (Zn,Mn)As layer forming
a honeycomb-like network. Magnetization measurements show that the sample
undergoes a ferromagnetic transition with a Curie temperature of 12 K and
\revision{magnetic moment reaches about 1.5 /Mn under = 5 T
and = 2 K}. Surprisingly, a colossal negative magnetoresistance, defined as
, up to 38\% under a low field of = 0.1
T and to 99.8\% under = 5 T, was observed at = 2 K. The
colossal magnetoresistance can be explained based on the Anderson localization
theory.Comment: Accepted for publication in EP
Treating Homeless Opioid Dependent Patients with Buprenorphine in an Office-Based Setting
CONTEXT
Although office-based opioid treatment with buprenorphine (OBOT-B) has been successfully implemented in primary care settings in the US, its use has not been reported in homeless patients.
OBJECTIVE
To characterize the feasibility of OBOT-B in homeless relative to housed patients.
DESIGN
A retrospective record review examining treatment failure, drug use, utilization of substance abuse treatment services, and intensity of clinical support by a nurse care manager (NCM) among homeless and housed patients in an OBOT-B program between August 2003 and October 2004. Treatment failure was defined as elopement before completing medication induction, discharge after medication induction due to ongoing drug use with concurrent nonadherence with intensified treatment, or discharge due to disruptive behavior.
RESULTS
Of 44 homeless and 41 housed patients enrolled over 12 months, homeless patients were more likely to be older, nonwhite, unemployed, infected with HIV and hepatitis C, and report a psychiatric illness. Homeless patients had fewer social supports and more chronic substance abuse histories with a 3- to 6-fold greater number of years of drug use, number of detoxification attempts and percentage with a history of methadone maintenance treatment. The proportion of subjects with treatment failure for the homeless (21%) and housed (22%) did not differ (P=.94). At 12 months, both groups had similar proportions with illicit opioid use [Odds ratio (OR), 0.9 (95% CI, 0.5–1.7) P=.8], utilization of counseling (homeless, 46%; housed, 49%; P=.95), and participation in mutual-help groups (homeless, 25%; housed, 29%; P=.96). At 12 months, 36% of the homeless group was no longer homeless. During the first month of treatment, homeless patients required more clinical support from the NCM than housed patients.
CONCLUSIONS
Despite homeless opioid dependent patients' social instability, greater comorbidities, and more chronic drug use, office-based opioid treatment with buprenorphine was effectively implemented in this population comparable to outcomes in housed patients with respect to treatment failure, illicit opioid use, and utilization of substance abuse treatment
Multi-Step Processing of Spatial Joins
Spatial joins are one of the most important operations for combining spatial objects of several relations. In this paper, spatial join processing is studied in detail for extended spatial objects in twodimensional data space. We present an approach for spatial join processing that is based on three steps. First, a spatial join is performed on the minimum bounding rectangles of the objects returning a set of candidates. Various approaches for accelerating this step of join processing have been examined at the last year’s conference [BKS 93a]. In this paper, we focus on the problem how to compute the answers from the set of candidates which is handled by
the following two steps. First of all, sophisticated approximations
are used to identify answers as well as to filter out false hits from
the set of candidates. For this purpose, we investigate various types
of conservative and progressive approximations. In the last step, the
exact geometry of the remaining candidates has to be tested against
the join predicate. The time required for computing spatial join
predicates can essentially be reduced when objects are adequately
organized in main memory. In our approach, objects are first decomposed
into simple components which are exclusively organized
by a main-memory resident spatial data structure. Overall, we
present a complete approach of spatial join processing on complex
spatial objects. The performance of the individual steps of our approach
is evaluated with data sets from real cartographic applications.
The results show that our approach reduces the total execution
time of the spatial join by factors
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The ATree: A data structure to support very large scientific databases
The datasets generated by satellite observations and supercomputer simulations are overwhelming conventional methods of storage and access, leading to unreasonably long delays in data analysis. The major problem that the authors address is the slow access, from large datasets in archival storage, to small subsets needed for scientific visualization and analysis. The goal is to minimize the amount of storage that has to be read when a subset of the data is needed. A second goal is to enhance the accessibility of data subsets by applying data reduction and indexing methods to the subsets. The reduced format allows larger datasets to be stored on local disk for analysis. Data indexing permits efficient manipulation of the data, and thus improves the productivity of the researcher. A data structure called the ATree is described that meets the demands of interactive scientific applications. The ATree data structure is suitable for storing data abstracts as well as original data. It allows quick access to a subset of interest and is suitable for feature-based queries. It intrinsically partitions the data and organizes the chunks in a linear sequence on secondary/tertiary storage. It can store data at various resolutions and incorporates hierarchical compression methods
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