Inferring offline hierarchical ties from online social networks

Social networks can represent many different types of relationships between actors, some explicit and some implicit. For example, email communications between users may be represented explicitly in a network, while managerial relationships may not. In this paper we focus on analyzing explicit interactions among actors in order to detect hierarchical social relationships that may be implicit. We start by employing three well-known ranking-based methods, PageRank, Degree Centrality, and Rooted-PageRank (RPR) to infer such implicit relationships from interactions between actors. Then we propose two novel approaches which take into account the time-dimension of interactions in the process of detecting hierarchical ties. We experiment on two datasets, the Enron email dataset to infer manager-subordinate relationships from email exchanges, and a scientific publication co-authorship dataset to detect PhD advisor-advisee relationships from paper co-authorships. Our experiments show that time-based methods perform considerably better than ranking-based methods. In the Enron dataset, they detect 48% of manager-subordinate ties versus 32% found by Rooted-PageRank. Similarly, in co-author dataset, they detect 62% of advisor-advisee ties compared to only 39% by Rooted-PageRank

A Strong X-Ray Burst from the Low Mass X-Ray Binary EXO0748-676

We have observed an unusually strong X-ray burst as a part of our regular eclipse timing observations of the low mass binary system EXO0748-676. The burst peak flux was 5.2x10^-8 ergs cm^-2 s^-1, approximately five times the normal peak X-ray burst flux observed from this source by RXTE. Spectral fits to the data strongly suggest that photospheric radius expansion occurred during the burst. In this Letter we examine the properties of this X-ray burst, which is the first example of a radius expansion burst from EXO0748-676 observed by RXTE. We find no evidence for coherent burst oscillations. Assuming that the peak burst luminosity is the Eddington luminosity for a 1.4 solar mass neutron star we derive a distance to EXO0748-676 of 7.7 kpc for a helium-dominated burst photosphere and 5.9 kpc for a hydrogen-dominated burst photosphere.Comment: 15 pages including 2 figures and 1 table. Accepted for publication in the Astrophysical Journa

How the Cervical Microbiota Contributes to Cervical Cancer Risk in Sub-Saharan Africa

Despite ongoing efforts, sub-Saharan Africa faces a higher cervical cancer burden than anywhere else in the world. Besides HPV infection, definitive factors of cervical cancer are still unclear. Particular states of the cervicovaginal microbiota and viral infections are associated with increased cervical cancer risk. Notably, HIV infection, which is prevalent in sub-Saharan Africa, greatly increases risk of cervicovaginal dysbiosis and cervical cancer. To better understand and address cervical cancer in sub-Saharan Africa, a better knowledge of the regional cervicovaginal microbiome is required This review establishes current knowledge of HPV, HIV, cervicovaginal infections, and the cervicovaginal microbiota in sub-Saharan Africa. Because population statistics are not available for the region, estimates are derived from smaller cohort studies. Microbiota associated with cervical inflammation have been found to be especially prevalent in sub-Saharan Africa, and to associate with increased cervical cancer risk. In addition to high prevalence and diversity of HIV and HPV, intracellular bacterial infections such as Chlamydia, Gonorrhea, and Mycoplasma hominis are much more common than in regions with a low burden of cervical cancer. This suggests the prevalence of cervical cancer in sub-Saharan Africa may be partially attributed to increased cervical inflammation resulting from higher likelihood of cervical infection and/or microbial dysbiosis

Generating Top-k packages via preference elicitation

There are several applications, such as play lists of songs or movies, and shopping carts, where users are interested in finding top-k packages, consisting of sets of items. In response to this need, there has been a recent urry of activity around extending classical recommender systems (RS), which are effective at recommending individual items, to recommend packages, or sets of items. The few recent proposals for package RS suffer from one of the following drawbacks: they either rely on hard constraints which may be difficult to be specified exactly by the user or on returning Paretooptimal packages which are too numerous for the user to sift through. To overcome these limitations, we propose an alternative approach for finding personalized top-k packages for users, by capturing users' preferences over packages using a linear utility function which the system learns. Instead of asking a user to specify this function explicitly, which is unrealistic, we explicitly model the uncertainty in the utility function and propose a preference elicitation-based framework for learning the utility function through feedback provided by the user. We propose several samplingbased methods which, given user feedback, can capture the updated utility function. We develop an efficient algorithm for generating top-k packages using the learned utility function, where the rank ordering respects any of a variety of ranking semantics proposed in the literature. Through extensive experiments on both real and synthetic datasets, we demonstrate the efficiency and effectiveness of the proposed system for finding top-k packages

Implementing flexible operators for regular path queries

Given the heterogeneity of complex graph data on the web, such as RDF linked data,a user wishing to query such data may lack full knowledge of its structure and irregularities. Hence, providing users with flexible querying capabilities can be beneficial. The query language we adopt comprises conjunctions of regular path queries, thus including extensions proposed for SPARQL 1.1 to allow for querying paths using regular expressions. To this language we add two operators: APPROX, supporting standard notions of approximation based on edit distance, and RELAX, which performs query relaxation based on RDFS inference rules. We describe our techniques for implementing the extended language and present a performance study undertaken on two real-world data sets. Our baseline implementation performs competitively with other automaton-based approaches, and we demonstrate empirically how various optimisations can decrease execution times of queries containing APPROX and RELAX, sometimes by orders of magnitude

Rapidly Converging Activity Expansions For Representing The Thermodynamic Properties Of Fluid Systems: Gases, Non-Electrolyte Solutions, Weak And Strong Electrolyte Solutions

For dilute gases and non-electrolyte solutions in the McMillan–Mayer standard state, an activity expansion due to Mayer has great advantages over the normal concentration expansion (virial equation) for strongly associating species. For weakly interacting systems, both approaches are suitable. The activity expansion eliminates the need to differentiate between strong “chemical” interactions and weak “physical” interactions since the same equation is used in each situation. The equation has been modified to represent electrolyte solutions in the McMillan–Mayer standard state by requiring that it be consistent with the Debye–Hückel and higher order limiting laws for strong electrolytes and that it be equivalent to a chemical association model for weak electrolytes. The result is a compact equation which contains no arbitrary ion-size parameters and which does not require the classification of an electrolyte as strong or weak. For 2:2 electrolytes, the equation gives a very good fit to the anomalous low concentration region. For practical thermodynamic calculations, similar equations for molal activity coefficients are proposed; good fits of the data are obtained

Freezing Points Of Aqueous Alcohols: Free Energy Of Interaction Of The CHOH, CH₂, CONH And C[double bond]C Functional Groups In Dilute Aqueous Solutions

The freezing temperatures of dilute aqueous solutions of methanol, ethanol, 2-propanol, butanol, t-butanol, cyclohexanol and ethylene glycol were measured over the concentration range 0.1 to 1 mol kg–1. Osmotic coefficients at 0°C were calculated. The limiting pairwise interaction coefficients of the alcohols, plus a variety of polyhydroxy compounds and carbohydrates, were calculated at 25°C from the available data and then correlated using the additivity principle of Savage and Wood. This correlation approximates effective free energies of CH2 and CHOH group interactions with themselves and with each other. Literature data were used to estimate interactions between CONH and C[double bond]C groups. The CONH—CONH interaction appears to be large, consistent with a strong stabilizing effect of these on native protein structures. The CH2…CH2 interaction also indicates attractive forces between these groups. The present model for the hydrophobic interaction is most appropriate for small molecular interactions whereas previous treatments are best for situations involving site binding. The CHOH…CHOH and CH2…CONH interactions are small, while the CHOH…CH2 free energy of interaction is positive, due either to volume exclusion or net repulsive forces. The entropy change associated with the CH2…CH2 interaction is large and positive as expected and is not completely compensated by a corresponding enthalpy change. The entropy change associated with the CONH…CONH interaction indicates that few degrees of freedom are involved, which is consistent with the formation of a strong hydrogen bond. The correlation can be used to estimate thermodynamic properties of dilute non-electrolyte solutions and can also predict the effect of solutes on the solubility of solids and gases