Scalable Text and Link Analysis with Mixed-Topic Link Models

Many data sets contain rich information about objects, as well as pairwise relations between them. For instance, in networks of websites, scientific papers, and other documents, each node has content consisting of a collection of words, as well as hyperlinks or citations to other nodes. In order to perform inference on such data sets, and make predictions and recommendations, it is useful to have models that are able to capture the processes which generate the text at each node and the links between them. In this paper, we combine classic ideas in topic modeling with a variant of the mixed-membership block model recently developed in the statistical physics community. The resulting model has the advantage that its parameters, including the mixture of topics of each document and the resulting overlapping communities, can be inferred with a simple and scalable expectation-maximization algorithm. We test our model on three data sets, performing unsupervised topic classification and link prediction. For both tasks, our model outperforms several existing state-of-the-art methods, achieving higher accuracy with significantly less computation, analyzing a data set with 1.3 million words and 44 thousand links in a few minutes.Comment: 11 pages, 4 figure

Latent Space Model for Multi-Modal Social Data

With the emergence of social networking services, researchers enjoy the increasing availability of large-scale heterogenous datasets capturing online user interactions and behaviors. Traditional analysis of techno-social systems data has focused mainly on describing either the dynamics of social interactions, or the attributes and behaviors of the users. However, overwhelming empirical evidence suggests that the two dimensions affect one another, and therefore they should be jointly modeled and analyzed in a multi-modal framework. The benefits of such an approach include the ability to build better predictive models, leveraging social network information as well as user behavioral signals. To this purpose, here we propose the Constrained Latent Space Model (CLSM), a generalized framework that combines Mixed Membership Stochastic Blockmodels (MMSB) and Latent Dirichlet Allocation (LDA) incorporating a constraint that forces the latent space to concurrently describe the multiple data modalities. We derive an efficient inference algorithm based on Variational Expectation Maximization that has a computational cost linear in the size of the network, thus making it feasible to analyze massive social datasets. We validate the proposed framework on two problems: prediction of social interactions from user attributes and behaviors, and behavior prediction exploiting network information. We perform experiments with a variety of multi-modal social systems, spanning location-based social networks (Gowalla), social media services (Instagram, Orkut), e-commerce and review sites (Amazon, Ciao), and finally citation networks (Cora). The results indicate significant improvement in prediction accuracy over state of the art methods, and demonstrate the flexibility of the proposed approach for addressing a variety of different learning problems commonly occurring with multi-modal social data.Comment: 12 pages, 7 figures, 2 table

An investigation of barriers to the use of the World Health Organization Surgical Safety Checklist in theatres

Background. The World Health Organization (WHO) has implemented the Surgical Safety Checklist (SSCL) as part of the Safe Surgery Saves Lives campaign. This is aimed at improving surgical safety worldwide. Despite many perceived benefits of the SSCL, compliance and acceptance in many areas remain poor.Objectives. To investigate perceptions of theatre staff regarding the checklist and to identify reasons and barriers for poor compliance and implementation.Methods. Questionnaires were handed out to theatre teams across all surgical disciplines at two large hospitals in Durban, South Africa, over a 2-week period. Data collected included role in theatre, intention of the SSCL, training received, as well as questions regarding previously identified barriers and staff perceptions.Results. Questionnaires were distributed to 225 practitioners, with a response rate of 81.7% from 51 nurses, 54 anaesthetists and 79 surgeons. Rank of medical staff included 52 seniors (consultants) and 81 juniors (registrars and medical officers). The majority (95%) of respondents perceived the SSCL as intended to improve safety, prevent errors or reduce morbidity and mortality. A total of 146 respondents (79.3%) received no SSCL training. No new barriers were identified, but previously identified barriers were confirmed. Our key factors were time-related issues and lack of buy-in from team members. Surgeons were perceived as being supportive by 45.1% of respondents, in contrast to nurses (62.5%), anaesthetists (70.1%) and management (68.5%). When compared with junior staff, senior staff were 5-fold more likely to feel that staff did not need to be trained and 8-fold more likely to indicate that the checklist did not improve patient safety.Conclusions. The WHO SSCL is an important tool in the operating room environment. The barriers in our setting are similar to those identified in other settings. There needs to be widespread training in the use of the SSCL, including adaptation of the checklist to make it fit for purpose in our setting. Improving use of the checklist will allow theatre staff to work together towards ensuring a safer theatre environment for both patients and staff

Geometrically Precise Building Blocks: the Self-Assembly of beta-Peptides

Peptides comprised entirely of b-amino acids, or b-peptides, have attracted substantial interest over the past 25 years due to their unique structural and chemical characteristics. b-Peptides form well-defined secondary structures that exhibit different geometries compared with their a-peptide counterparts, giving rise to their foldamer classification. b-Peptide foldamers can be functionalized easily and are metabolically stable and, together with the predictable side-chain topography, have led to the design of a growing number of bioactive b-peptides with a range of biological targets. The strategic engineering of chemical and topographic properties has also led to the design of b-peptide mimics of higher-order oligomers. More recently, the ability of these peptides to self-assemble into complex structures of controlled geometries has been exploited in materials applications. The focus of thismini-review is on how the unique structural features of b-peptide assemblies have been exploited in the design of self-assembled proteomimetic bundles and nanomaterials

Critical care triage during the COVID-19 pandemic in South Africa: A constitutional imperative!

Triage and rationing of scarce intensive care unit (ICU) resources are an unavoidable necessity. In routine circumstances, ICU triage is premised on the best interests of an individual patient; however, when increased demand exceeds capacity, as during an infectious disease outbreak, healthcare providers need to make difficult decisions to benefit the broader community while still respecting individual interests. We are currently living through an unprecedented period, with South Africa (SA) facing the challenges of the global COVID-19 pandemic. The Critical Care Society of Southern Africa (CCSSA) expedited the development of a triage guidance document to inform the appropriate and fair use of scarce ICU resources during this pandemic. Triage decision-making is based on the clinical odds of a positive ICU outcome, balanced against the risk of mortality and longer-term morbidity affecting quality of life. Factors such as age and comorbid conditions are considered for their potential impact on clinical outcome, but are never the sole criteria for denying ICU-level care. Arbitrary, unfair discrimination is never condoned. The CCSSA COVID-19 triage guideline is aligned with SA law and international ethical standards, and upholds respect for all persons. The Bill of Rights, however, does not mandate the level of care enshrined in the constitutional right to healthcare. ICU admission is not always appropriate, available or feasible for every person suffering critical illness or injury; however, everyone has the right to receive appropriate healthcare at another level. If ICU resources are used for people who do not stand to benefit, this effectively denies others access to potentially life-saving healthcare. Appropriate triaging can therefore be considered a constitutional imperative

Token Jumping in minor-closed classes

Given two $k$-independent sets $I$ and $J$ of a graph $G$, one can ask if it is possible to transform the one into the other in such a way that, at any step, we replace one vertex of the current independent set by another while keeping the property of being independent. Deciding this problem, known as the Token Jumping (TJ) reconfiguration problem, is PSPACE-complete even on planar graphs. Ito et al. proved in 2014 that the problem is FPT parameterized by $k$ if the input graph is $K_{3,\ell}$-free. We prove that the result of Ito et al. can be extended to any $K_{\ell,\ell}$-free graphs. In other words, if $G$ is a $K_{\ell,\ell}$-free graph, then it is possible to decide in FPT-time if $I$ can be transformed into $J$. As a by product, the TJ-reconfiguration problem is FPT in many well-known classes of graphs such as any minor-free class

Reconfiguring Independent Sets in Claw-Free Graphs

We present a polynomial-time algorithm that, given two independent sets in a claw-free graph $G$, decides whether one can be transformed into the other by a sequence of elementary steps. Each elementary step is to remove a vertex $v$ from the current independent set $S$ and to add a new vertex $w$ (not in $S$) such that the result is again an independent set. We also consider the more restricted model where $v$ and $w$ have to be adjacent

Resistivity as a function of temperature for models with hot spots on the Fermi surface.

We calculate the resistivity $\rho$ as a function of temperature $T$ for two models currently discussed in connection with high temperature superconductivity: nearly antiferromagnetic Fermi liquids and models with van Hove singularities on the Fermi surface. The resistivity is calculated semiclassicaly by making use of a Boltzmann equation which is formulated as a variational problem. For the model of nearly antiferromagnetic Fermi liquids we construct a better variational solution compared to the standard one and we find a new energy scale for the crossover to the $\rho\propto T^2$ behavior at low temperatures. This energy scale is finite even when the spin-fluctuations are assumed to be critical. The effect of additional impurity scattering is discussed. For the model with van Hove singularities a standard ansatz for the Boltzmann equation is sufficient to show that although the quasiparticle lifetime is anomalously short, the resistivity $\rho\propto T^2\ln(1/T)$.Comment: Revtex 3.0, 8 pages; figures available upon request. Submitted to Phys. Rev. B