Titlebook: Smoking and Lung Inflammation; Basic, Pre-Clinical Thomas J. Rogers,Gerard J. Criner,William D. Cornw Book 2013 Springer Science+Business

Mets552

Infectious Mechanisms Regulating Susceptibility to Acute Exacerbations of COPD,

抑制

Anti-Inflammatory Therapeutics in COPD: Past, Present, and Future,

MAZE

, they are not applicable to ontologies in more expressive description logics. In this paper, we propose a novel NCES approach which extends the state of the art to the description logic .. Our extension, dubbed NCES2, comes with an improved training data generator and does not require pretrained em

Prologue

Incommensurate

William D. Cornwell Ph.D.,Maria Elena Vega M.D.,Thomas J. Rogers Ph.D.pture expressiveness by re-scaling parameters of normalization. We propose Kullback-Leibler(KL) Regularized normalization (KL-Norm) which make the normalized data well behaved and helps in better generalization as it reduces over-fitting, generalises well on out of domain distributions and removes i

責(zé)怪

Paul A. Kennedy,Laurie E. Kilpatricke fusion strategy is eventually tailor-made for sophisticated table representations. In this way, the table structure and semantic information are well considered with dual-graph modeling. Consequently, the input query can match the target tables based on their full-fledged table representations and

Blood-Clot

Common-Migraine

Changcheng Song Ph.D.,Steven G. Kelsen M.D.ing curve of the sequential decision strategy We introduce a computationally simplified solving method, ., an algorithm that walks along the edges of the polytope representing the objective function. Simulations results show that the proposed online learning algorithm outperforms baseline offline me

Anticoagulant

David B. Corry M.D.,Farrah Kheradmand are connected through which cols. Thus, a natural hierarchy on the peaks arises by the question which higher peak comes behind the col, yielding to chains of peaks with increasing heights. The resulting “l(fā)ine parent hierarchy” displays dominance relations between important vertices. We show that ne

火海

Alex J. Mackay M.B.B.S., M.R.C.P.,Anant R. C. Patel M.B.B.S., M.R.C.P.,Jadwiga A. Wedzicha M.D. F.R.ces and, as a result, simultaneously extracts latent higher-order spatio-temporal dependencies. We provide theoretical foundations behind the proposed hyper-simplex-graph representation learning and validate our new Hodge-style Hyper-simplex-graph Neural Networks (H.-Nets) on 7 real world spatio-tem