411 research outputs found
Selfish Network Creation with Non-Uniform Edge Cost
Network creation games investigate complex networks from a game-theoretic
point of view. Based on the original model by Fabrikant et al. [PODC'03] many
variants have been introduced. However, almost all versions have the drawback
that edges are treated uniformly, i.e. every edge has the same cost and that
this common parameter heavily influences the outcomes and the analysis of these
games.
We propose and analyze simple and natural parameter-free network creation
games with non-uniform edge cost. Our models are inspired by social networks
where the cost of forming a link is proportional to the popularity of the
targeted node. Besides results on the complexity of computing a best response
and on various properties of the sequential versions, we show that the most
general version of our model has constant Price of Anarchy. To the best of our
knowledge, this is the first proof of a constant Price of Anarchy for any
network creation game.Comment: To appear at SAGT'1
Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees
Deep Reinforcement Learning (DRL) has achieved impressive success in many
applications. A key component of many DRL models is a neural network
representing a Q function, to estimate the expected cumulative reward following
a state-action pair. The Q function neural network contains a lot of implicit
knowledge about the RL problems, but often remains unexamined and
uninterpreted. To our knowledge, this work develops the first mimic learning
framework for Q functions in DRL. We introduce Linear Model U-trees (LMUTs) to
approximate neural network predictions. An LMUT is learned using a novel
on-line algorithm that is well-suited for an active play setting, where the
mimic learner observes an ongoing interaction between the neural net and the
environment. Empirical evaluation shows that an LMUT mimics a Q function
substantially better than five baseline methods. The transparent tree structure
of an LMUT facilitates understanding the network's learned knowledge by
analyzing feature influence, extracting rules, and highlighting the
super-pixels in image inputs.Comment: This paper is accepted by ECML-PKDD 201
Association of Caldendrin splice isoforms with secretory vesicles in neurohypophyseal axons and the pituitary
AbstractCaldendrin is a neuronal calcium-binding protein, which is highly enriched in the postsynaptic density fraction and exhibits a prominent somato-dendritic distribution in brain. Two additional splice variants derive from the caldendrin gene, which have unrelated N-termini and were previously only detected in the retina. We now show that these isoforms are present in neurohypophyseal axons and on secretory granules of endocrine cells. In light of the described interaction of the Caldendrin C-terminus with Q-type Cav2.1 calcium channels these data suggest that this interaction takes place in neurohypophyseal axons and pituitary cells indicating functions of the short splice variants in triggering Ca2+ transients to a vesicular target interaction
Estimation of bubble-mediated air–sea gas exchange from concurrent DMS and CO2 transfer velocities at intermediate–high wind speeds
Simultaneous air–sea fluxes and concentration differences of dimethylsulfide (DMS) and carbon dioxide (CO2) were measured during a summertime North Atlantic cruise in 2011. This data set reveals significant differences between the gas transfer velocities of these two gases (Δkw) over a range of wind speeds up to 21 m s−1. These differences occur at and above the approximate wind speed threshold when waves begin breaking. Whitecap fraction (a proxy for bubbles) was also measured and has a positive relationship with Δkw, consistent with enhanced bubble-mediated transfer of the less soluble CO2 relative to that of the more soluble DMS. However, the correlation of Δkw with whitecap fraction is no stronger than with wind speed. Models used to estimate bubble-mediated transfer from in situ whitecap fraction underpredict the observations, particularly at intermediate wind speeds. Examining the differences between gas transfer velocities of gases with different solubilities is a useful way to detect the impact of bubble-mediated exchange. More simultaneous gas transfer measurements of different solubility gases across a wide range of oceanic conditions are needed to understand the factors controlling the magnitude and scaling of bubble-mediated gas exchange
Probabilistic modeling and machine learning in structural and systems biology
This supplement contains extended versions of a selected subset of papers presented at the workshop PMSB 2007, Probabilistic Modeling and Machine Learning in Structural and Systems Biology, Tuusula, Finland, from June 17 to 18, 2006
The band structure of BeTe - a combined experimental and theoretical study
Using angle-resolved synchrotron-radiation photoemission spectroscopy we have
determined the dispersion of the valence bands of BeTe(100) along ,
i.e. the [100] direction. The measurements are analyzed with the aid of a
first-principles calculation of the BeTe bulk band structure as well as of the
photoemission peaks as given by the momentum conserving bulk transitions.
Taking the calculated unoccupied bands as final states of the photoemission
process, we obtain an excellent agreement between experimental and calculated
spectra and a clear interpretation of almost all measured bands. In contrast,
the free electron approximation for the final states fails to describe the BeTe
bulk band structure along properly.Comment: 21 pages plus 4 figure
Context-dependent effects on spatial variation in deer-vehicle collisions
Identifying factors that contribute to the risk of wildlife‐vehicle collisions (WVCs) has been a key focus of wildlife managers, transportation safety planners and road ecologists for over three decades. Despite these efforts, few generalities have emerged which can help predict the occurrence of WVCs, heightening the uncertainty under which conservation, wildlife and transportation management decisions are made. Undermining this general understanding is the use of study area boundaries that are incongruent with major biophysical gradients, inconsistent data collection protocols among study areas and species‐specific interactions with roads. We tested the extent to which factors predicting the occurrence of deer‐vehicle collisions (DVCs) were general among five study areas distributed over a 11,400‐km2 region in the Canadian Rocky Mountains. In spite of our system‐wide focus on the same genus (i.e., Odocoileus hemionus and O. virginianus), study area delineation along major biophysical gradients, and use of consistent data collection protocols, we found that large‐scale biophysical processes influence the effect of localized factors. At the local scale, factors predicting WVC occurrence varied greatly between individual study areas. Distance to water was an important predictor of WVCs in three of the five study areas, while other variables had modest importance in only two of the five study areas. Thus, lack of generality in factors predicting WVCs may have less to do with methodological or taxonomic differences among study areas than the large‐scale, biophysical context within which the data were collected. These results highlight the critical need to develop a conceptual framework in road ecology that can unify the disparate results emerging from field studies on WVC occurrence
Genome-Wide DNA Methylation Profiling in Early Stage I Lung Adenocarcinoma Reveals Predictive Aberrant Methylation in the Promoter Region of the Long Noncoding RNA PLUT: An Exploratory Study
Introduction: Surgical procedure is the treatment of choice in early stage I lung adenocarcinoma. However, a considerable number of patients experience recurrence within the first 2 years after complete resection. Suitable prognostic biomarkers that identify patients at high risk of recurrence (who may probably benefit from adjuvant treatment) are still not available. This study aimed at identifying methylation markers for early recurrence that may become important tools for the development of new treatment modalities. Methods: Genome-wide DNA methylation profiling was performed on 30 stage I lung adenocarcinomas, comparing 14 patients with early metastatic recurrence with 16 patients with a long-term relapse-free survival period using methylated-CpG-immunoprecipitation followed by high-throughput next-generation sequencing. The differentially methylated regions between the two subgroups were validated for their prognostic value in two independent cohorts using the MassCLEAVE assay, a high-resolution quantitative methylation analysis. Results: Unsupervised clustering of patients in the discovery cohort on the basis of differentially methylated regions identified patients with shorter relapse-free survival (hazard ratio: 2.23; 95% confidence interval: 0.66-7.53; p = 0.03). In two validation cohorts, promoter hypermethylation of the long noncoding RNA PLUT was significantly associated with shorter relapse-free survival (hazard ratio: 0.54; 95% confidence interval: 0.31-0.93; p < 0.026) and could be reported as an independent prognostic factor in the multivariate Cox regression analysis. Conclusions: Promoter hypermethylation of the long noncoding RNA PLUT is predictive in patients with early stage I adenocarcinoma at high risk for early recurrence. Further studies are needed to validate its role in carcinogenesis and its use as a biomarker to facilitate patient selection and risk stratification
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