Escape times for subgraph detection and graph partitioning

We provide a rearrangement based algorithm for fast detection of subgraphs of $k$ vertices with long escape times for directed or undirected networks. Complementing other notions of densest subgraphs and graph cuts, our method is based on the mean hitting time required for a random walker to leave a designated set and hit the complement. We provide a new relaxation of this notion of hitting time on a given subgraph and use that relaxation to construct a fast subgraph detection algorithm and a generalization to $K$-partitioning schemes. Using a modification of the subgraph detector on each component, we propose a graph partitioner that identifies regions where random walks live for comparably large times. Importantly, our method implicitly respects the directed nature of the data for directed graphs while also being applicable to undirected graphs. We apply the partitioning method for community detection to a large class of model and real-world data sets.Comment: 22 pages, 10 figures, 1 table, comments welcome!

A metric on directed graphs and Markov chains based on hitting probabilities

The shortest-path, commute time, and diffusion distances on undirected graphs have been widely employed in applications such as dimensionality reduction, link prediction, and trip planning. Increasingly, there is interest in using asymmetric structure of data derived from Markov chains and directed graphs, but few metrics are specifically adapted to this task. We introduce a metric on the state space of any ergodic, finite-state, time-homogeneous Markov chain and, in particular, on any Markov chain derived from a directed graph. Our construction is based on hitting probabilities, with nearness in the metric space related to the transfer of random walkers from one node to another at stationarity. Notably, our metric is insensitive to shortest and average walk distances, thus giving new information compared to existing metrics. We use possible degeneracies in the metric to develop an interesting structural theory of directed graphs and explore a related quotienting procedure. Our metric can be computed in $O(n^3)$ time, where $n$ is the number of states, and in examples we scale up to $n=10,000$ nodes and $\approx 38M$ edges on a desktop computer. In several examples, we explore the nature of the metric, compare it to alternative methods, and demonstrate its utility for weak recovery of community structure in dense graphs, visualization, structure recovering, dynamics exploration, and multiscale cluster detection.Comment: 26 pages, 9 figures, for associated code, visit https://github.com/zboyd2/hitting_probabilities_metric, accepted at SIAM J. Math. Data Sc

Reframing e-assessment: building professional nursing and academic attributes in a first year nursing course

This paper documents the relationships between pedagogy and e-assessment in two nursing courses offered at the University of Southern Queensland, Australia. The courses are designed to build the academic, numeracy and technological attributes student nurses need if they are to succeed at university and in the nursing profession. The paper first outlines the management systems supporting the two courses and how they intersect with the e-learning and e-assessment components of course design. These pedagogical choices are then reviewed. While there are lessons to be learnt and improvements to be made, preliminary results suggest students and staff are extremely supportive of the courses. The e-assessment is very positively received with students reporting increased confidence and competency in numeracy, as well as IT, academic, research and communication skills

Academic freedom in Europe: time for a Magna Charta?

This paper is a preliminary attempt to establish a working definition of academic freedom for the European Union states. The paper details why such a definition is required for the European Union and then examines some of the difficulties of defining academic freedom. By drawing upon experience of the legal difficulties beset by the concept in the USA and building on previous analyses of constitutional and legislative protection for academic freedom, and of legal regulations concerning institutional governance and academic tenure, a working definition of academic freedom is then derived. The resultant definition which, it is suggested, could form the basis for a European Magna Charta Libertatis Academicae, goes beyond traditional discussions of academic freedom by specifying not only the rights inherent in the concept but also its accompanying duties, necessary limitations and safeguards. The paper concludes with proposals for how the definition might be tested and carried forward

Deep-coverage whole genome sequences and blood lipids among 16,324 individuals.

Large-scale deep-coverage whole-genome sequencing (WGS) is now feasible and offers potential advantages for locus discovery. We perform WGS in 16,324 participants from four ancestries at mean depth >29X and analyze genotypes with four quantitative traits-plasma total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol, and triglycerides. Common variant association yields known loci except for few variants previously poorly imputed. Rare coding variant association yields known Mendelian dyslipidemia genes but rare non-coding variant association detects no signals. A high 2M-SNP LDL-C polygenic score (top 5th percentile) confers similar effect size to a monogenic mutation (~30 mg/dl higher for each); however, among those with severe hypercholesterolemia, 23% have a high polygenic score and only 2% carry a monogenic mutation. At these sample sizes and for these phenotypes, the incremental value of WGS for discovery is limited but WGS permits simultaneous assessment of monogenic and polygenic models to severe hypercholesterolemia

Reducing corruption in a Mexican medical school: impact assessment across two cross-sectional surveys

<p>Abstract</p> <p>Background</p> <p>Corruption pervades educational and other institutions worldwide and medical schools are not exempt. Empirical evidence about levels and types of corruption in medical schools is sparse. We conducted surveys in 2000 and 2007 in the medical school of the Autonomous University of Guerrero in Mexico to document student perceptions and experience of corruption and to support the medical school to take actions to tackle corruption.</p> <p>Methods</p> <p>In both 2000 and 2007 medical students completed a self-administered questionnaire in the classroom without the teacher present. The questionnaire asked about unofficial payments for admission to medical school, for passing an examination and for administrative procedures. We examined factors related to the experience of corruption in multivariate analysis. Focus groups of students discussed the quantitative findings.</p> <p>Results</p> <p>In 2000, 6% of 725 responding students had paid unofficially to obtain entry into the medical school; this proportion fell to 1.6% of the 436 respondents in 2007. In 2000, 15% of students reported having paid a bribe to pass an examination, not significantly different from the 18% who reported this in 2007. In 2007, students were significantly more likely to have bribed a teacher to pass an examination if they were in the fourth year, if they had been subjected to sexual harassment or political pressure, and if they had been in the university for five years or more. Students resented the need to make unofficial payments and suggested tackling the problem by disciplining corrupt teachers. The university administration made several changes to the system of admissions and examinations in the medical school, based on the findings of the 2000 survey.</p> <p>Conclusion</p> <p>The fall in the rate of bribery to enter the medical school was probably the result of the new admissions system instituted after the first survey. Further actions will be necessary to tackle the continuing presence of bribery to pass examinations and for administrative procedures. The social audit helped to draw attention to corruption and to stimulate actions to tackle it.</p

Publisher Correction: Deep coverage whole genome sequences and plasma lipoprotein(a) in individuals of European and African ancestries.

The original version of this article contained an error in the name of the author Ramachandran S. Vasan, which was incorrectly given as Vasan S. Ramachandran. This has now been corrected in both the PDF and HTML versions of the article

Deep coverage whole genome sequences and plasma lipoprotein(a) in individuals of European and African ancestries.

Lipoprotein(a), Lp(a), is a modified low-density lipoprotein particle that contains apolipoprotein(a), encoded by LPA, and is a highly heritable, causal risk factor for cardiovascular diseases that varies in concentrations across ancestries. Here, we use deep-coverage whole genome sequencing in 8392 individuals of European and African ancestry to discover and interpret both single-nucleotide variants and copy number (CN) variation associated with Lp(a). We observe that genetic determinants between Europeans and Africans have several unique determinants. The common variant rs12740374 associated with Lp(a) cholesterol is an eQTL for SORT1 and independent of LDL cholesterol. Observed associations of aggregates of rare non-coding variants are largely explained by LPA structural variation, namely the LPA kringle IV 2 (KIV2)-CN. Finally, we find that LPA risk genotypes confer greater relative risk for incident atherosclerotic cardiovascular diseases compared to directly measured Lp(a), and are significantly associated with measures of subclinical atherosclerosis in African Americans

Predictors of Performance during a 161 km Mountain Footrace

Training volume and cardiovascular dynamics influence endurance performance. However, there is limited information on the interplay between training volume, cardiovascular dynamics, and performance in ultra-marathon athletes. PURPOSE: We aimed to determine predictors of performance in finishers of the 2023 Western States Endurance Run (WSER). METHODS: Sixty participants who finished the race (49 males/11 females; mean age: 44.7 ± 9.6 y, range: 26–66 y; BMI: 22.7 ± 2.2 kg/m2) completed pre-race surveys including average training volume (AV) and peak training volume (PV), as well as resting cardiovascular measures including resting heart rate (RHR) and augmentation index (AIx), a measure of wave reflection characteristics. Based on WSER completion time, we calculated average running velocity (RV). We assessed associations among 22 variables using bivariate correlation analysis (Pearson’s Correlation for normally distributed data and Spearman’s Rank Correlation if normality was not met). Within our listed variables, normality was met in age and AV. Additionally, we completed multiple regression analyses for predictors. We present descriptive data as mean ± SD. RESULTS: Participants had an average RV of 6.33 ± 0.97 km/h (3.93 ± 0.6 mph), and reported an AV of 91.9 ± 24.5 km/wk (57.1 ± 15.2 miles/wk) and a PV of 141.0 ± 47.2 km/wk (87.6 ± 29.3 miles/wk). We observed significant associations between RV and age (r(58) = -0.57, p r(58) = 0.41, p r(58) = 0.34, p R2 = 0.37; F(3,56) = 12.4, pb1 = 0.013; t(56) = 2.57, p = 0.013), resulting in a 0.33 km/h increase in RV for every 25-km increase in AV. Last, significant relations existed between RV and AIx (r(58) = -0.30, p = 0.022); and RHR (r(58) = -0.26, p = 0.046). CONCLUSION: We found that (1) average weekly training volume is a significant predictor of performance in elite ultra-marathon athletes and (2) race performance was inversely associated with resting arterial wave reflection characteristics and heart rate