G-CREWE: Graph CompREssion With Embedding for Network Alignment

Network alignment is useful for multiple applications that require increasingly large graphs to be processed. Existing research approaches this as an optimization problem or computes the similarity based on node representations. However, the process of aligning every pair of nodes between relatively large networks is time-consuming and resource-intensive. In this paper, we propose a framework, called G-CREWE (Graph CompREssion With Embedding) to solve the network alignment problem. G-CREWE uses node embeddings to align the networks on two levels of resolution, a fine resolution given by the original network and a coarse resolution given by a compressed version, to achieve an efficient and effective network alignment. The framework first extracts node features and learns the node embedding via a Graph Convolutional Network (GCN). Then, node embedding helps to guide the process of graph compression and finally improve the alignment performance. As part of G-CREWE, we also propose a new compression mechanism called MERGE (Minimum dEgRee neiGhbors comprEssion) to reduce the size of the input networks while preserving the consistency in their topological structure. Experiments on all real networks show that our method is more than twice as fast as the most competitive existing methods while maintaining high accuracy.Comment: 10 pages, accepted at the 29th ACM International Conference onInformation and Knowledge Management (CIKM 20

Leveraging Graph Diffusion Models for Network Refinement Tasks

Most real-world networks are noisy and incomplete samples from an unknown target distribution. Refining them by correcting corruptions or inferring unobserved regions typically improves downstream performance. Inspired by the impressive generative capabilities that have been used to correct corruptions in images, and the similarities between "in-painting" and filling in missing nodes and edges conditioned on the observed graph, we propose a novel graph generative framework, SGDM, which is based on subgraph diffusion. Our framework not only improves the scalability and fidelity of graph diffusion models, but also leverages the reverse process to perform novel, conditional generation tasks. In particular, through extensive empirical analysis and a set of novel metrics, we demonstrate that our proposed model effectively supports the following refinement tasks for partially observable networks: T1: denoising extraneous subgraphs, T2: expanding existing subgraphs and T3: performing "style" transfer by regenerating a particular subgraph to match the characteristics of a different node or subgraph.Comment: Work in Progress. 21 pages, 7 figure

Cyprus' image—a sun and sea destination—as a detrimental factor to seasonal fluctuations. Exploration into motivational factors for holidaying in Cyprus

Cyprus is established as a summer destination. To aid the destination in developing its winter season as well, this research uses a qualitative inductive approach to explore the tourists’ current image of the island and their motivations of visiting it. The research indicates that the current image, which essentially portrays Cyprus as a sun-and-sea destination is thought to dissuade tourists from perceiving the island as a year-round destination. Nonetheless, increasing the pull factors of the destination through the development of unique special interest products can help in extending the tourism season as well as broaden its narrow image

Internet use, eHealth literacy and attitudes toward computer/internet among people with schizophrenia spectrum disorders: a cross-sectional study in two distant European regions

Background: Individuals with schizophrenia spectrum disorders use the Internet for general and health-related purposes. Their ability to find, understand, and apply the health information they acquire online in order to make appropriate health decisions-known as eHealth literacy-has never been investigated. The European agenda strives to limit health inequalities and enhance mental health literacy. Nevertheless, each European member state varies in levels of Internet use and online health information-seeking. This study aimed to examine computer/Internet use for general and health-related purposes, eHealth literacy, and attitudes toward computer/Internet among adults with schizophrenia spectrum disorders from two distant European regions.Methods: Data were collected from mental health services of psychiatric clinics in Finland (FI) and Greece (GR). A total of 229 patients (FI = 128, GR = 101) participated in the questionnaire survey. The data analysis included evaluation of frequencies and group comparisons with multiple linear and logistic regression models.Results: The majority of Finnish participants were current Internet users (FI = 111, 87%, vs. GR = 33, 33%, P<.0001), while the majority of Greek participants had never used computers/Internet, mostly due to their perception that they do not need it. In both countries, more than half of Internet users used the Internet for health-related purposes (FI = 61, 55%, vs. GR = 20, 61%). The eHealth literacy of Internet users (previous and current Internet users) was found significantly higher in the Finnish group (FI: Mean = 27.05, SD 5.36; GR: Mean = 23.15, SD = 7.23, P<. 0001) upon comparison with their Greek counterparts. For current Internet users, Internet use patterns were significantly different between country groups. When adjusting for gender, age, education and disease duration, country was a significant predictor of frequency of Internet use, eHealth literacy and Interest. The Finnish group of Internet users scored higher in eHealth literacy, while the Greek group of never Internet users had a higher Interest in computer/Internet.Conclusions: eHealth literacy is either moderate (Finnish group) or low (Greek group). Thus, exposure to ICT and eHealth skills training are needed for this population. Recommendations to improve the eHealth literacy and access to health information among these individuals are provided

Demographic predictors of wellbeing in Carers of people with psychosis: secondary analysis of trial data

Background: Carers of people with psychosis are at a greater risk of physical and mental health problems compared to the general population. Yet, not all carers will experience a decline in health. This predicament has provided the rationale for research studies exploring what factors predict poor wellbeing in carers of people with psychosis. Our study builds on previous research by testing the predictive value of demographic variables on carer wellbeing within a single regression model. Methods: To achieve this aim, we conducted secondary analysis on two trial data sets that were merged and recoded for the purposes of this study. Results: Contrary to our hypotheses, only carer gender and age predicted carer wellbeing; with lower levels of carer wellbeing being associated with being female or younger (aged under 50). However, the final regression model explained only 11% of the total variance. Conclusions: Suggestions for future research are discussed in light of the limitations inherent in secondary analysis studies. Further research is needed where sample sizes are sufficient to explore the interactive and additive impact of other predictor variables

A simplified (modified) Duke Activity Status Index (M-DASI) to characterise functional capacity: A secondary analysis of the Measurement of Exercise Tolerance before Surgery (METS) study

Background Accurate assessment of functional capacity, a predictor of postoperative morbidity and mortality, is essential to improving surgical planning and outcomes. We assessed if all 12 items of the Duke Activity Status Index (DASI) were equally important in reflecting exercise capacity. Methods In this secondary cross-sectional analysis of the international, multicentre Measurement of Exercise Tolerance before Surgery (METS) study, we assessed cardiopulmonary exercise testing and DASI data from 1455 participants. Multivariable regression analyses were used to revise the DASI model in predicting an anaerobic threshold (AT) >11 ml kg −1 min −1 and peak oxygen consumption (VO 2 peak) >16 ml kg −1 min −1, cut-points that represent a reduced risk of postoperative complications. Results Five questions were identified to have dominance in predicting AT>11 ml kg −1 min −1 and VO 2 peak>16 ml.kg −1min −1. These items were included in the M-DASI-5Q and retained utility in predicting AT>11 ml.kg −1.min −1 (area under the receiver-operating-characteristic [AUROC]-AT: M-DASI-5Q=0.67 vs original 12-question DASI=0.66) and VO 2 peak (AUROC-VO2 peak: M-DASI-5Q 0.73 vs original 12-question DASI 0.71). Conversely, in a sensitivity analysis we removed one potentially sensitive question related to the ability to have sexual relations, and the ability of the remaining four questions (M-DASI-4Q) to predict an adequate functional threshold remained no worse than the original 12-question DASI model. Adding a dynamic component to the M-DASI-4Q by assessing the chronotropic response to exercise improved its ability to discriminate between those with VO 2 peak>16 ml.kg −1.min −1 and VO 2 peak<16 ml.kg −1.min −1. Conclusions The M-DASI provides a simple screening tool for further preoperative evaluation, including with cardiopulmonary exercise testing, to guide perioperative management

Integration of the Duke Activity Status Index into preoperative risk evaluation: a multicentre prospective cohort study.

BACKGROUND: The Duke Activity Status Index (DASI) questionnaire might help incorporate self-reported functional capacity into preoperative risk assessment. Nonetheless, prognostically important thresholds in DASI scores remain unclear. We conducted a nested cohort analysis of the Measurement of Exercise Tolerance before Surgery (METS) study to characterise the association of preoperative DASI scores with postoperative death or complications. METHODS: The analysis included 1546 participants (≥40 yr of age) at an elevated cardiac risk who had inpatient noncardiac surgery. The primary outcome was 30-day death or myocardial injury. The secondary outcomes were 30-day death or myocardial infarction, in-hospital moderate-to-severe complications, and 1 yr death or new disability. Multivariable logistic regression modelling was used to characterise the adjusted association of preoperative DASI scores with outcomes. RESULTS: The DASI score had non-linear associations with outcomes. Self-reported functional capacity better than a DASI score of 34 was associated with reduced odds of 30-day death or myocardial injury (odds ratio: 0.97 per 1 point increase above 34; 95% confidence interval [CI]: 0.96-0.99) and 1 yr death or new disability (odds ratio: 0.96 per 1 point increase above 34; 95% CI: 0.92-0.99). Self-reported functional capacity worse than a DASI score of 34 was associated with increased odds of 30-day death or myocardial infarction (odds ratio: 1.05 per 1 point decrease below 34; 95% CI: 1.00-1.09), and moderate-to-severe complications (odds ratio: 1.03 per 1 point decrease below 34; 95% CI: 1.01-1.05). CONCLUSIONS: A DASI score of 34 represents a threshold for identifying patients at risk for myocardial injury, myocardial infarction, moderate-to-severe complications, and new disability

Contemporary Management of Locally Advanced and Recurrent Rectal Cancer: Views from the PelvEx Collaborative

Pelvic exenteration is a complex operation performed for locally advanced and recurrent pelvic cancers. The goal of surgery is to achieve clear margins, therefore identifying adjacent or involved organs, bone, muscle, nerves and/or vascular structures that may need resection. While these extensive resections are potentially curative, they can be associated with substantial morbidity. Recently, there has been a move to centralize care to specialized units, as this facilitates better multi-disciplinary care input. Advancements in pelvic oncology and surgical innovation have redefined the boundaries of pelvic exenterative surgery. Combined with improved neoadjuvant therapies, advances in diagnostics, and better reconstructive techniques have provided quicker recovery and better quality of life outcomes, with improved survival This article provides highlights of the current management of advanced pelvic cancers in terms of surgical strategy and potential future developments

A systematic review evaluating the psychometric properties of measures of social inclusion

Introduction: Improving social inclusion opportunities for population health has been identified as a priority area for international policy. There is a need to comprehensively examine and evaluate the quality of psychometric properties of measures of social inclusion that are used to guide social policy and outcomes. Objective: To conduct a systematic review of the literature on all current measures of social inclusion for any population group, to evaluate the quality of the psychometric properties of identified measures, and to evaluate if they capture the construct of social inclusion. Methods: A systematic search was performed using five electronic databases: CINAHL, PsycINFO, Embase, ERIC and Pubmed and grey literature were sourced to identify measures of social inclusion. The psychometric properties of the social inclusion measures were evaluated against the COSMIN taxonomy of measurement properties using pre-set psychometric criteria. Results: Of the 109 measures identified, twenty-five measures, involving twenty-five studies and one manual met the inclusion criteria. The overall quality of the reviewed measures was variable, with the Social and Community Opportunities Profile-Short, Social Connectedness Scale and the Social Inclusion Scale demonstrating the strongest evidence for sound psychometric quality. The most common domain included in the measures was connectedness (21), followed by participation (19); the domain of citizenship was covered by the least number of measures (10). No single instrument measured all aspects within the three domains of social inclusion. Of the measures with sound psychometric evidence, the Social and Community Opportunities Profile-Short captured the construct of social inclusion best. Conclusions: The overall quality of the psychometric properties demonstrate that the current suite of available instruments for the measurement of social inclusion are promising but need further refinement. There is a need for a universal working definition of social inclusion as an overarching construct for ongoing research in the area of the psychometric properties of social inclusion instruments