Extending local features with contextual information in graph kernels

Graph kernels are usually defined in terms of simpler kernels over local substructures of the original graphs. Different kernels consider different types of substructures. However, in some cases they have similar predictive performances, probably because the substructures can be interpreted as approximations of the subgraphs they induce. In this paper, we propose to associate to each feature a piece of information about the context in which the feature appears in the graph. A substructure appearing in two different graphs will match only if it appears with the same context in both graphs. We propose a kernel based on this idea that considers trees as substructures, and where the contexts are features too. The kernel is inspired from the framework in [6], even if it is not part of it. We give an efficient algorithm for computing the kernel and show promising results on real-world graph classification datasets.Comment: To appear in ICONIP 201

Metopic Suture – Incidence and Morphology in South Indian Human Adult Skulls

Background:In the present study, the objectives were to determine the incidence of persistence of metopic sutures, their shape and extent in south Indian human adult skulls.Methods: The study was conducted on 100 human adult dry skulls which belong to the museum of the department of Forensic medicine & toxicology and the department of Anatomy, JJM Medical College, Davangere, Karnataka. The metopic sutures were classified as complete and incomplete types. The incomplete was divided into linear, ‘V’ shaped and ‘U’ shaped, which were further divided into three groups as present in the lower part of the frontal bone, in the upper part, and in the middle part.Results: From our observations, the metopic suture was present in 13 (13%) cases. The complete metopic suture was seen in 6 skulls (6%) and incomplete one in 7 (7%). Among the incomplete ones, linear was found in 5 (5%), ‘V’ shaped in 1 (1%) and ‘U’ shaped type in 1 (1%) cases. In 7 (7%), cases it was observed in the lower part of frontal bone, but no suture remnant was found in the upper and lower part of frontal bone.Conclusion: Due to the paucity in the availability of the skulls, a lesser number of sample size was taken in our study. But a good analysis can be done with a larger sample size, to give a constructive data

DeepWalk: Online Learning of Social Representations

We present DeepWalk, a novel approach for learning latent representations of vertices in a network. These latent representations encode social relations in a continuous vector space, which is easily exploited by statistical models. DeepWalk generalizes recent advancements in language modeling and unsupervised feature learning (or deep learning) from sequences of words to graphs. DeepWalk uses local information obtained from truncated random walks to learn latent representations by treating walks as the equivalent of sentences. We demonstrate DeepWalk's latent representations on several multi-label network classification tasks for social networks such as BlogCatalog, Flickr, and YouTube. Our results show that DeepWalk outperforms challenging baselines which are allowed a global view of the network, especially in the presence of missing information. DeepWalk's representations can provide $F_1$ scores up to 10% higher than competing methods when labeled data is sparse. In some experiments, DeepWalk's representations are able to outperform all baseline methods while using 60% less training data. DeepWalk is also scalable. It is an online learning algorithm which builds useful incremental results, and is trivially parallelizable. These qualities make it suitable for a broad class of real world applications such as network classification, and anomaly detection.Comment: 10 pages, 5 figures, 4 table

Impact of proctoring on success rates for percutaneous revascularisation of coronary chronic total occlusions.

OBJECTIVE: To assess the impact of proctoring for chronic total occlusion (CTO) percutaneous coronary intervention (PCI) in six UK centres. METHODS: We retrospectively analysed 587 CTO procedures from six UK centres and compared success rates of operators who had received proctorship with success rates of the same operators before proctorship (pre-proctored) and operators in the same institutions who had not been proctored (non-proctored). There were 232 patients in the pre-proctored/non-proctored group and 355 patients in the post-proctored group. Complexity was assessed by calculating the Japanese CTO (JCTO) score for each case. RESULTS: CTO PCI success was greater in the post-proctored compared with the pre-proctored/non-proctored group (77.5% vs 62.1%, p<0.0001). In more complex cases where JCTO≥2, the difference in success was greater (70.7% vs 49.5%, p=0.0003). After proctoring, there was an increase in CTO PCI activity in centres from 2.5% to 3.5%, p<0.0001 (as a proportion of total PCI), and the proportion of very difficult cases with JCTO score ≥3 increased from 15.3% (35/229) to 29.7% (105/354), p<0.0001. CONCLUSIONS: Proctoring resulted in an increase in procedural success for CTO PCI, an increase in complex CTO PCI and an increase in total CTO PCI activity. Proctoring may be a valuable way to improve access to CTO PCI and the likelihood of procedural success

The complexity of the Pk partition problem and related problems in bipartite graphs

International audienceIn this paper, we continue the investigation made in [MT05] about the approximability of Pk partition problems, but focusing here on their complexity. Precisely, we aim at designing the frontier between polynomial and NP-complete versions of the Pk partition problem in bipartite graphs, according to both the constant k and the maximum degree of the input graph. We actually extend the obtained results to more general classes of problems, namely, the minimum k-path partition problem and the maximum Pk packing problem. Moreover, we propose some simple approximation algorithms for those problems

Using graph-kernels to represent semantic information in text classification

Most text classification systems use bag-of-words represen- tation of documents to find the classification target function. Linguistic structures such as morphology, syntax and semantic are completely ne- glected in the learning process. This paper proposes a new document representation that, while includ- ing its context independent sentence meaning, is able to be used by a structured kernel function, namely the direct product kernel. The proposal is evaluated using a dataset of articles from a Portuguese daily newspaper and classifiers are built using the SVM algorithm. The results show that this structured representation, while only partially de- scribing document’s significance has the same discriminative power over classes as the traditional bag-of-words approach

Hierarchies and Ranks for Persistence Pairs

We develop a novel hierarchy for zero-dimensional persistence pairs, i.e., connected components, which is capable of capturing more fine-grained spatial relations between persistence pairs. Our work is motivated by a lack of spatial relationships between features in persistence diagrams, leading to a limited expressive power. We build upon a recently-introduced hierarchy of pairs in persistence diagrams that augments the pairing stored in persistence diagrams with information about which components merge. Our proposed hierarchy captures differences in branching structure. Moreover, we show how to use our hierarchy to measure the spatial stability of a pairing and we define a rank function for persistence pairs and demonstrate different applications.Comment: Topology-based Methods in Visualization 201

Silica-Encapsulated Efficient and Stable Si Quantum Dots with High Biocompatibility

A facile fabrication method to produce biocompatible semiconductor Quantum Dots encapsulated in high quality and thick thermal oxide is presented. The process employs sonication of porous Si/SiO2 structures to produce flakes with dimension in the 50–200 nm range. These flakes show a coral-like SiO2 skeleton with Si nanocrystals embedded in and are suitable for functionalization with other diagnostic or therapeutic agents. Silicon is a biocompatible material, efficiently cleared from the human body. The Photoluminescence emission falls in the transparency window for living tissues and is found to be bright and stable for hours in the aggressive biological environment

Low Levels of Genetic Divergence across Geographically and Linguistically Diverse Populations from India

Ongoing modernization in India has elevated the prevalence of many complex genetic diseases associated with a western lifestyle and diet to near-epidemic proportions. However, although India comprises more than one sixth of the world's human population, it has largely been omitted from genomic surveys that provide the backdrop for association studies of genetic disease. Here, by genotyping India-born individuals sampled in the United States, we carry out an extensive study of Indian genetic variation. We analyze 1,200 genome-wide polymorphisms in 432 individuals from 15 Indian populations. We find that populations from India, and populations from South Asia more generally, constitute one of the major human subgroups with increased similarity of genetic ancestry. However, only a relatively small amount of genetic differentiation exists among the Indian populations. Although caution is warranted due to the fact that United States–sampled Indian populations do not represent a random sample from India, these results suggest that the frequencies of many genetic variants are distinctive in India compared to other parts of the world and that the effects of population heterogeneity on the production of false positives in association studies may be smaller in Indians (and particularly in Indian-Americans) than might be expected for such a geographically and linguistically diverse subset of the human population