227 research outputs found
Sequential equilibrium in monotone games: theory-based analysis of experimental data
A monotone game is an extensive-form game with complete information,
simultaneous moves and an irreversibility structure on strategies.
It captures a variety of situations in which players make partial
commitments and allows us to characterize conditions under which
equilibria result in socially desirable outcomes. However, since the
game has many equilibrium outcomes, the theory lacks predictive power.
To produce stronger predictions, one can restrict attention to the set of
sequential equilibria, or Markov equilibria, or symmetric equilibria, or
pure-strategy equilibria. This paper explores the relationship between
equilibrium behavior in a class of monotone games, namely voluntary contribution games, and the behavior of human subjects in an experimental
setting. We find evidence of both pure- and mixed-strategy
equilibria and several key features of the symmetric Markov perfect
equilibrium (SMPE) in the data. To judge how well the SMPE fits the
data, we estimate a model of Quantal Response Equilibrium (QRE)
(McKelvey and Palfrey 1995, 1998) and find that the decision rules of
the QRE model are qualitatively very similar to the empirical choice
probabilities
Network architecture, salience and coordination
This paper reports the results of an experimental investigation of
monotone games with imperfect information. Players are located at
the nodes of a network and observe the actions of other players only if
they are connected by the network. These games have many sequential
equilibria; nonetheless, the behavior of subjects in the laboratory is
predictable. The network architecture makes some strategies salient
and this in turn makes the subjects’ behavior predictable and facilitates
coordination on efficient outcomes. In some cases, modal behavior
corresponds to equilibrium strategies
Greedy Selfish Network Creation
We introduce and analyze greedy equilibria (GE) for the well-known model of
selfish network creation by Fabrikant et al.[PODC'03]. GE are interesting for
two reasons: (1) they model outcomes found by agents which prefer smooth
adaptations over radical strategy-changes, (2) GE are outcomes found by agents
which do not have enough computational resources to play optimally. In the
model of Fabrikant et al. agents correspond to Internet Service Providers which
buy network links to improve their quality of network usage. It is known that
computing a best response in this model is NP-hard. Hence, poly-time agents are
likely not to play optimally. But how good are networks created by such agents?
We answer this question for very simple agents. Quite surprisingly, naive
greedy play suffices to create remarkably stable networks. Specifically, we
show that in the SUM version, where agents attempt to minimize their average
distance to all other agents, GE capture Nash equilibria (NE) on trees and that
any GE is in 3-approximate NE on general networks. For the latter we also
provide a lower bound of 3/2 on the approximation ratio. For the MAX version,
where agents attempt to minimize their maximum distance, we show that any
GE-star is in 2-approximate NE and any GE-tree having larger diameter is in
6/5-approximate NE. Both bounds are tight. We contrast these positive results
by providing a linear lower bound on the approximation ratio for the MAX
version on general networks in GE. This result implies a locality gap of
for the metric min-max facility location problem, where n is the
number of clients.Comment: 28 pages, 8 figures. An extended abstract of this work was accepted
at WINE'1
Coordination of Mobile Mules via Facility Location Strategies
In this paper, we study the problem of wireless sensor network (WSN)
maintenance using mobile entities called mules. The mules are deployed in the
area of the WSN in such a way that would minimize the time it takes them to
reach a failed sensor and fix it. The mules must constantly optimize their
collective deployment to account for occupied mules. The objective is to define
the optimal deployment and task allocation strategy for the mules, so that the
sensors' downtime and the mules' traveling distance are minimized. Our
solutions are inspired by research in the field of computational geometry and
the design of our algorithms is based on state of the art approximation
algorithms for the classical problem of facility location. Our empirical
results demonstrate how cooperation enhances the team's performance, and
indicate that a combination of k-Median based deployment with closest-available
task allocation provides the best results in terms of minimizing the sensors'
downtime but is inefficient in terms of the mules' travel distance. A
k-Centroid based deployment produces good results in both criteria.Comment: 12 pages, 6 figures, conferenc
Detection of Prion Protein in Urine-Derived Injectable Fertility Products by a Targeted Proteomic Approach
BACKGROUND: Iatrogenic transmission of human prion disease can occur through medical or surgical procedures, including injection of hormones such as gonadotropins extracted from cadaver pituitaries. Annually, more than 300,000 women in the United States and Canada are prescribed urine-derived gonadotropins for infertility. Although menopausal urine donors are screened for symptomatic neurological disease, incubation of Creutzfeldt-Jakob disease (CJD) is impossible to exclude by non-invasive testing. Risk of carrier status of variant CJD (vCJD), a disease associated with decades-long peripheral incubation, is estimated to be on the order of 100 per million population in the United Kingdom. Studies showing infectious prions in the urine of experimental animals with and without renal disease suggest that prions could be present in asymptomatic urine donors. Several human fertility products are derived from donated urine; recently prion protein has been detected in preparations of human menopausal gonadotropin (hMG). METHODOLOGY/PRINCIPAL FINDINGS: Using a classical proteomic approach, 33 and 34 non-gonadotropin proteins were identified in urinary human chorionic gonadotropin (u-hCG) and highly-purified urinary human menopausal gonadotropin (hMG-HP) products, respectively. Prion protein was identified as a major contaminant in u-hCG preparations for the first time. An advanced prion protein targeted proteomic approach was subsequently used to conduct a survey of gonadotropin products; this approach detected human prion protein peptides in urine-derived injectable fertility products containing hCG, hMG and hMG-HP, but not in recombinant products. CONCLUSIONS/SIGNIFICANCE: The presence of protease-sensitive prion protein in urinary-derived injectable fertility products containing hCG, hMG, and hMG-HP suggests that prions may co-purify in these products. Intramuscular injection is a relatively efficient route of transmission of human prion disease, and young women exposed to prions can be expected to survive an incubation period associated with a minimal inoculum. The risks of urine-derived fertility products could now outweigh their benefits, particularly considering the availability of recombinant products
A Prediction Model to Prioritize Individuals for a SARS-CoV-2 Test Built from National Symptom Surveys
Background: The gold standard for COVID-19 diagnosis is detection of viral RNA through PCR. Due to global limitations in testing capacity, effective prioritization of individuals for testing is essential. Methods: We devised a model estimating the probability of an individual to test positive for COVID-19 based on answers to 9 simple questions that have been associated with SARS-CoV-2 infection. Our model was devised from a subsample of a national symptom survey that was answered over 2 million times in Israel in its first 2 months and a targeted survey distributed to all residents of several cities in Israel. Overall, 43,752 adults were included, from which 498 self-reported as being COVID-19 positive. Findings: Our model was validated on a held-out set of individuals from Israel where it achieved an auROC of 0.737 (CI: 0.712–0.759) and auPR of 0.144 (CI: 0.119–0.177) and demonstrated its applicability outside of Israel in an independently collected symptom survey dataset from the US, UK, and Sweden. Our analyses revealed interactions between several symptoms and age, suggesting variation in the clinical manifestation of the disease in different age groups. Conclusions: Our tool can be used online and without exposure to suspected patients, thus suggesting worldwide utility in combating COVID-19 by better directing the limited testing resources through prioritization of individuals for testing, thereby increasing the rate at which positive individuals can be identified. Moreover, individuals at high risk for a positive test result can be isolated prior to testing. Funding: E.S. is supported by the Crown Human Genome Center, Larson Charitable Foundation New Scientist Fund, Else Kroener Fresenius Foundation, White Rose International Foundation, Ben B. and Joyce E. Eisenberg Foundation, Nissenbaum Family, Marcos Pinheiro de Andrade and Vanessa Buchheim, Lady Michelle Michels, and Aliza Moussaieff and grants funded by the Minerva foundation with funding from the Federal German Ministry for Education and Research and by the European Research Council and the Israel Science Foundation. H.R. is supported by the Israeli Council for Higher Education (CHE) via the Weizmann Data Science Research Center and by a research grant from Madame Olga Klein – Astrachan
Economic impact of infections and antibiotics
In this chapter, we review several aspects with respect to the burden of infectious diseases, its impact in morbidity and mortality, and its economic burden. Furthermore, we referenced the actual situation with relation to the use of antimicrobial, the resistance problem and misuse of antibiotic, and the economic impact in the health systems
Colorectal cancer in inflammatory bowel disease: Results of the 3rd ECCO pathogenesis scientific workshop (I)
Cellular mechanisms in basic and clinical gastroenterology and hepatolog
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