Select, Link and Rank: Diversified Query Expansion and Entity Ranking using Wikipedia

A search query, being a very concise grounding of user intent, could potentially have many possible interpretations. Search engines hedge their bets by diversifying top results to cover multiple such possibilities so that the user is likely to be satisfied, whatever be her intended interpretation. Diversified Query Expansion is the problem of diversifying query expansion suggestions, so that the user can specialize the query to better suit her intent, even before perusing search results. We propose a method, Select-Link-Rank, that exploits semantic information from Wikipedia to generate diversified query expansions. SLR does collective processing of terms and Wikipedia entities in an integrated framework, simultaneously diversifying query expansions and entity recommendations. SLR starts with selecting informative terms from search results of the initial query, links them to Wikipedia entities, performs a diversity-conscious entity scoring and transfers such scoring to the term space to arrive at query expansion suggestions. Through an extensive empirical analysis and user study, we show that our method outperforms the state-of-the-art diversified query expansion and diversified entity recommendation techniques.

Clustering-based Query Routing in Cooperative Semi-structured Peer to Peer Networks

We consider the problem of resource selection in clustered Peer-to-Peer Information Retrieval (P2P IR) networks with cooperative peers. The clustered P2P IR framework presents a significant departure from general P2P IR architectures by employing clustering to ensure content coherence between resources at the resource selection layer, without disturbing document allocation. We propose that such a property could be leveraged in resource selection by adapting well-studied and popular inverted lists for centralized document retrieval. Accordingly, we propose the Inverted PeerCluster Index (IPI), an approach that adapts the inverted lists, in a straightforward manner, for resource selection in clustered P2P IR. IPI also encompasses a strikingly simple peer-specific scoring mechanism that exploits the said index for resource selection. Through an extensive empirical analysis on P2P IR testbeds, we establish that IPI competes well with the sophisticated state-of-the-art methods in virtually every parameter of interest for the resource selection task, in the context of clustered P2P IR.

Severe Israeli Spotted Fever with Multiorgan Failure in a Child

An increased risk of severe and fatal Israeli spotted fever (ISF) has been observed in adults, mostly associated with ISF strain. Here, we report a case of severe ISF with multiorgan failure in a Portuguese child.

Top-K Query Processing in Edge-Labeled Graph Data

Edge-labeled graphs have proliferated rapidly over the last decade due to the increased popularity of social networks and the Semantic Web. In social networks, relationships between people are represented by edges and each edge is labeled with a semantic annotation. Hence, a huge single graph can express many different relationships between entities. The Semantic Web represents each single fragment of knowledge as a triple (subject, predicate, object), which is conceptually identical to an edge from subject to object labeled with predicates. A set of triples constitutes an edge-labeled graph on which knowledge inference is performed. Subgraph matching has been extensively used as a query language for patterns in the context of edge-labeled graphs. For example, in social networks, users can specify a subgraph matching query to find all people that have certain neighborhood relationships. Heavily used fragments of the SPARQL query language for the Semantic Web and graph queries of other graph DBMS can also be viewed as subgraph matching over large graphs. Though subgraph matching has been extensively studied as a query paradigm in the Semantic Web and in social networks, a user can get a large number of answers in response to a query. These answers can be shown to the user in accordance with an importance ranking. In this thesis proposal, we present four different scoring models along with scalable algorithms to find the top-k answers via a suite of intelligent pruning techniques. The suggested models consist of a practically important subset of the SPARQL query language augmented with some additional useful features. The first model called Substitution Importance Query (SIQ) identifies the top-k answers whose scores are calculated from matched vertices' properties in each answer in accordance with a user-specified notion of importance. The second model called Vertex Importance Query (VIQ) identifies important vertices in accordance with a user-defined scoring method that builds on top of various subgraphs articulated by the user. Approximate Importance Query (AIQ), our third model, allows partial and inexact matchings and returns top-k of them with a user-specified approximation terms and scoring functions. In the fourth model called Probabilistic Importance Query (PIQ), a query consists of several sub-blocks: one mandatory block that must be mapped and other blocks that can be opportunistically mapped. The probability is calculated from various aspects of answers such as the number of mapped blocks, vertices' properties in each block and so on and the most top-k probable answers are returned. An important distinguishing feature of our work is that we allow the user a huge amount of freedom in specifying: (i) what pattern and approximation he considers important, (ii) how to score answers - irrespective of whether they are vertices or substitution, and (iii) how to combine and aggregate scores generated by multiple patterns and/or multiple substitutions. Because so much power is given to the user, indexing is more challenging than in situations where additional restrictions are imposed on the queries the user can ask. The proposed algorithms for the first model can also be used for answering SPARQL queries with ORDER BY and LIMIT, and the method for the second model also works for SPARQL queries with GROUP BY, ORDER BY and LIMIT. We test our algorithms on multiple real-world graph databases, showing that our algorithms are far more efficient than popular triple stores.

Homomorphic encryption and database query privacy

Homomorphic encryption is a particular type of encryption method that enables computing over encrypted data. This has a wide range of real world ramifications such as being able to blindly compute a search result sent to a remote server without revealing its content. In the first part of this thesis, we discuss how database search queries can be made secure using a homomorphic encryption scheme based on the ideas of Gahi et al. Gahi’s method is based on the integer-based fully homomorphic encryption scheme proposed by Dijk et al. We propose a new database search scheme called the Homomorphic Query Processing Scheme, which can be used with the ring-based fully homomorphic encryption scheme proposed by Braserski. In the second part of this thesis, we discuss the cybersecurity of the smart electric grid. Specifically, we use the Homomorphic Query Processing scheme to construct a keyword search technique in the smart grid. Our work is based on the Public Key Encryption with Keyword Search (PEKS) method introduced by Boneh et al. and a Multi-Key Homomorphic Encryption scheme proposed by L´opez-Alt et al. A summary of the results of this thesis (specifically the Homomorphic Query Processing Scheme) is published at the 14th Canadian Workshop on Information Theory (CWIT).

Fever, Hemiparesis and Hyponatraemia in a 63-year-old. HIV, another Great Masquerader?

The authors describe the unusual case of a 63-year-old patient who was referred with fever and lethargy, and was found to be hyponatraemic. The patient subsequently developed hemiparesis, and neuroradiology showed several space-occupying brain lesions. The cause was later identified as cerebral toxoplasmosis in undiagnosed Acquired Immunodeficiency Syndrome (AIDS).

A Young Woman with Fever and Cervical Lymphadenopathy

Kikuchi-Fujimoto's disease is a self-limiting and rare disorder of unknown aetiology. The typical presentation includes fever, cervical lymphadenopathy and night sweats. Consequently, it is part of the differential diagnosis of infectious, lymphoproliferative and connective tissue diseases. Histology demonstrates necrotizing histiocytic lymphadenitis. Treatment is symptomatic with non-steroidal antiinflammatory agents, although there are reports of corticosteroid use in complicated cases. We present the case of a 23-year-old woman admitted to hospital for fever and cervical lymphadenopathies, and diagnosed with Kikuchi-Fujimoto's disease.

Hepcidin and Ferritin Levels in Fever of Unknown Origin: Is There a New Biomarker?

Background and objectives: Significantly elevated serum ferritin levels are associated with both iron overload and some inflammatory conditions. Hepcidin is a protein that interferes with iron absorption in inflammatory states and acts as an acute-phase reactant. Materials and methods: Here we report the case a 33-year-old patient who presented with high fever, skin lesions and arthralgia lasting for 2 weeks. His ferritin level was 13,800 µg/l and his hepcidin level was 61 ng/dl. Results: The final diagnosis was adult onset Still's disease. The condition evolved satisfactorily with steroid treatment, but after several weeks the patient presented with an unexpected recurrence. Conclusions: Hepcidin is a good inflammatory marker that could be useful in the differential diagnosis of hyperferritinaemia.

Acute Q Fever Presenting with Multi-Organ Failure: Re-Evaluation of the Initial Diagnosis

We present the case of a 48-year-old man admitted to the critical care unit with atrial fibrillation, and acute heart and kidney failure accompanied by coagulopathy and an abnormal liver test. Initially diagnosed as a non-ST elevation myocardial infarction, re-evaluation of the case led to the consideration of severe sepsis. Q fever and leptospirosis were the most probable causes and empiric treatment was initiated. A complete recovery was achieved following treatment.

Investigating novel approaches to the detection of virus neutralising antibodies to rabies and Rift Valley fever virus

Serosurveillance is a powerful tool fundamental to understanding infectious disease dynamics. The presence of virus neutralising antibody (VNAb) in sera is considered the best evidence of infection, or indeed vaccination, and the gold standard serological assay for their detection is the virus neutralisation test (VNT). However, VNTs are labour intensive, costly and time consuming. In addition, VNTs for the detection of antibodies to highly pathogenic viruses require the use of high containment facilities, restricting the application of these assays to the few laboratories with adequate facilities. As a result, robust serological data on such viruses are limited. In this thesis I develop novel VNTs for the detection of VNAb to two important, highly pathogenic, zoonotic viruses; rabies and Rift Valley fever virus (RVFV). The pseudotype-based neutralisation test developed in this study allows for the detection of rabies VNAb without the requirement for high containment facilities. This assay was utilised to investigate the presence of rabies VNAb in animals from a variety of ecological settings. In this thesis I present evidence of natural rabies infection in both domestic dogs and lions from rabies endemic settings. The assay was further used to investigate the kinetics of VNAb response to rabies vaccination in a cohort of free-roaming dogs. The RVFV neutralisation assay developed herein utilises a recombinant luciferase expressing RVFV, which allows for rapid, high-throughput serosurveillance of this important neglected pathogen. In this thesis I present evidence of RVFV infection in a variety of domestic and wildlife species from Northern Tanzania, in addition to the detection of low-level transmission of RVFV during interepidemic periods. Additionally, the investigation of a longitudinal cohort of domestic livestock also provided evidence of rapid waning of RVF VNAb following natural infection. Collectively, the serological data presented in this thesis are consistent with existing data in the literature generated using the gold standard VNTs. Increasing the availability of serological assays will allow the generation of robust serological data, which are imperative to enhancing our understanding of the complex, multi-host ecology of these two viruses.

An Information Theoretic Approach to Automatic Query Expansion

International audience

Searching for return: How Google search engine query data can beat the market

Throughout the last years technologic improvements have enabled internet users to analyze and retrieve data regarding Internet searches. In several fields of study this data has been used. Some authors have been using search engine query data to forecast economic variables, to detect influenza areas or to demonstrate that it is possible to capture some patterns in stock markets indexes. In this paper one investment strategy is presented using Google Trends’ weekly query data from major global stock market indexes’ constituents. The results suggest that it is indeed possible to achieve higher Info Sharpe ratios, especially for the major European stock market indexes in comparison to those provided by a buy-and-hold strategy for the period considered.

Rickettsia amblyommii infecting Amblyomma sculptum in endemic spotted fever area from southeastern Brazil

The Rickettsia bacteria include the aetiological agents for the human spotted fever (SF) disease. In the present study, a SF group Rickettsia amblyommii related bacterium was detected in a field collected Amblyomma sculptum ( Amblyomma cajennense species complex) tick from a Brazilian SF endemic site in southeastern Brazil, in the municipality of Juiz de Fora, state of Minas Gerais. Genetic analysis based on genes ompA, ompB and htrA showed that the detected strain, named R. amblyommii str. JF, is related to the species R. amblyommii.

Primary dengue haemorrhagic fever in patients from northeast of Brazil is associated with high levels of interferon-b during acute phase

Dengue is an acute febrile disease caused by the mosquito-borne dengue virus (DENV) that according to clinical manifestations can be classified as asymptomatic, mild or severe dengue. Severe dengue cases have been associated with an unbalanced immune response characterised by an over secretion of inflammatory cytokines. In the present study we measured type I interferon (IFN-I) transcript and circulating levels in primary and secondary DENV infected patients. We observed that dengue fever (DF) and dengue haemorrhagic fever (DHF) patients express IFN-I differently. While DF and DHF patients express interferon-a similarly (52,71 ± 7,40 and 49,05 ± 7,70, respectively), high levels of circulating IFN-b were associated with primary DHF patients. On the other hand, secondary DHF patients were not able to secrete large amounts of IFN-b which in turn may have influenced the high-level of viraemia. Our results suggest that, in patients from our cohort, infection by DENV serotype 3 elicits an innate response characterised by higher levels of IFN-b in the DHF patients with primary infection, which could contribute to control infection evidenced by the low-level of viraemia in these patients. The present findings may contribute to shed light in the role of innate immune response in dengue pathogenesis.