1,370 research outputs found
On the extraction of disjunctive landmarks from planning problems via symmetry reduction
The exploitation of symmetry in combinatorial search has typically focused on using information about symmetries to control search. This work describes an approach that exploits symmetry to get more detailed domain-analysis rather than as a method of search control
Identification and characterization of a homozygous deletion found in ovarian ascites by representational difference analysis
Recurrent Latent Variable Networks for Session-Based Recommendation
In this work, we attempt to ameliorate the impact of data sparsity in the
context of session-based recommendation. Specifically, we seek to devise a
machine learning mechanism capable of extracting subtle and complex underlying
temporal dynamics in the observed session data, so as to inform the
recommendation algorithm. To this end, we improve upon systems that utilize
deep learning techniques with recurrently connected units; we do so by adopting
concepts from the field of Bayesian statistics, namely variational inference.
Our proposed approach consists in treating the network recurrent units as
stochastic latent variables with a prior distribution imposed over them. On
this basis, we proceed to infer corresponding posteriors; these can be used for
prediction and recommendation generation, in a way that accounts for the
uncertainty in the available sparse training data. To allow for our approach to
easily scale to large real-world datasets, we perform inference under an
approximate amortized variational inference (AVI) setup, whereby the learned
posteriors are parameterized via (conventional) neural networks. We perform an
extensive experimental evaluation of our approach using challenging benchmark
datasets, and illustrate its superiority over existing state-of-the-art
techniques
Cystic fibrosis mice carrying the missense mutation G551D replicate human genotype phenotype correlations
We have generated a mouse carrying the human G551D mutation in the cystic fibrosis transmembrane conductance regulator gene (CFTR) by a one-step gene targeting procedure. These mutant mice show cystic fibrosis pathology but have a reduced risk of fatal intestinal blockage compared with 'null' mutants, in keeping with the reduced incidence of meconium ileus in G551D patients. The G551D mutant mice show greatly reduced CFTR-related chloride transport, displaying activity intermediate between that of cftr(mlUNC) replacement ('null') and cftr(mlHGU) insertional (residual activity) mutants and equivalent to approximately 4% of wild-type CFTR activity. The long-term survival of these animals should provide an excellent model with which to study cystic fibrosis, and they illustrate the value of mouse models carrying relevant mutations for examining genotype-phenotype correlations
An Interactive Narrative Platform for Story Understanding Experiments
Interactive Narratives are systems that use automated narrative generation
techniques to create multiple story variants which can be
shown to an audience, as virtual narratives, using cinematic staging
techniques. The focus of previous research has included aspects
such as the quality of automatically generated narratives and the
way in which audiences respond to them. However in this work we
have developed a mechanism for control of interactive narratives
that supports their use in experiments to assess story understanding.
This is implemented in our demonstration system, which features
two parts: an interface that allows high-level specification of criteria
for story understanding experiments; and a participant interface in
which virtual narratives, conforming to the experimental design, are
presented as 3D visualizations. The virtual narrative is based on a
pre-existing children’s story, and features a cast of virtual characters
Revisiting Clifford algebras and spinors III: conformal structures and twistors in the paravector model of spacetime
This paper is the third of a series of three, and it is the continuation of
math-ph/0412074 and math-ph/0412075. After reviewing the conformal spacetime
structure, conformal maps are described in Minkowski spacetime as the twisted
adjoint representation of the group Spin_+(2,4), acting on paravectors.
Twistors are then presented via the paravector model of Clifford algebras and
related to conformal maps in the Clifford algebra over the lorentzian R{4,1}$
spacetime. We construct twistors in Minkowski spacetime as algebraic spinors
associated with the Dirac-Clifford algebra Cl(1,3)(C) using one lower spacetime
dimension than standard Clifford algebra formulations, since for this purpose
the Clifford algebra over R{4,1} is also used to describe conformal maps,
instead of R{2,4}. Although some papers have already described twistors using
the algebra Cl(1,3)(C), isomorphic to Cl(4,1), the present formulation sheds
some new light on the use of the paravector model and generalizations.Comment: 17 page
Creation and Worldwide Utilisation of New COVID-19 Online Information Hub for Genetics Health Professionals, Patients and Families
The current COVID-19 pandemic has unfortunately resulted in many significant concerns for individuals with genetic disorders and their relatives, regarding the viral infection and, particularly, its specific implications and additional advisable precautions for individuals affected by genetic disorders. To address this, the resulting requirement for guidance and information for the public and for genetics professionals was discussed among colleagues nationally, on the ScotGEN Steering Committee, and internationally on the Education Committee of the European Society of Human Genetics (ESHG). It was agreed that the creation of an online hub of genetics-related COVID-19 information resources would be particularly helpful. The proposed content, divided into a web page for professionals and a page for patients, was discussed with, and approved by, genetics professionals. The hub was created and provided online at www.scotgen.org.uk and linked from the ESHG’s educational website for genetics and genomics, at www.eurogems.org. The new hub provides links, summary information and representative illustrations for a wide range of selected international resources. The resources for professionals include: COVID-19 research related hubs provided by Nature, Science, Frontiers, and PubMed; clinical guidelines; the European Centre for Disease Prevention and Control; the World Health Organisation; and molecular data sources including coronavirus 3D protein structures. The resources for patients and families include links to many accessible sources of support and relevant information. Since the launch of the pages, the website has received visits from over 50 countries worldwide. Several genetics consultants have commented on usefulness, clarity, readability, and ease of navigation. Visits have originated most frequently in the United Kingdom, Kuwait, Hong Kong, Moldova, United States, Philippines, France, and Qatar. More links have been added since the launch of the hub to include additional international public health and academic resources. In conclusion, an up-to-date online hub has been created and made freely available for healthcare professionals, patients, relatives and the public, providing categorised easily navigated links to a range of worldwide resources related to COVID-19. These pages are receiving a rapidly growing number of return visits and the authors continue to maintain and update the pages’ content, incorporating new developments in this field of enormous worldwide importance
- …