DDSL: Efficient Subgraph Listing on Distributed and Dynamic Graphs

Subgraph listing is a fundamental problem in graph theory and has wide applications in areas like sociology, chemistry, and social networks. Modern graphs can usually be large-scale as well as highly dynamic, which challenges the efficiency of existing subgraph listing algorithms. Recent works have shown the benefits of partitioning and processing big graphs in a distributed system, however, there is only few work targets subgraph listing on dynamic graphs in a distributed environment. In this paper, we propose an efficient approach, called Distributed and Dynamic Subgraph Listing (DDSL), which can incrementally update the results instead of running from scratch. DDSL follows a general distributed join framework. In this framework, we use a Neighbor-Preserved storage for data graphs, which takes bounded extra space and supports dynamic updating. After that, we propose a comprehensive cost model to estimate the I/O cost of listing subgraphs. Then based on this cost model, we develop an algorithm to find the optimal join tree for a given pattern. To handle dynamic graphs, we propose an efficient left-deep join algorithm to incrementally update the join results. Extensive experiments are conducted on real-world datasets. The results show that DDSL outperforms existing methods in dealing with both static dynamic graphs in terms of the responding time

'The smoking toolkit study': a national study of smoking and smoking cessation in England

Background: Up-to-date data tracking of national smoking patterns and cessation-related behaviour is required to evaluate and inform tobacco control strategies. The Smoking Toolkit Study (STS) was designed for this role. This paper describes the methodology of the STS and examines as far as possible the representativeness of the samples.Methods: The STS consists of monthly, cross sectional household interviews of adults aged 16 and over in England with smokers and recent ex-smokers in each monthly wave followed up by postal questionnaires three and six months later. Between November 2006 and December 2010 the baseline survey was completed by 90,568 participants. STS demographic, prevalence and cigarette consumption estimates are compared with those from the Health Survey for England (HSE) and the General Lifestyle Survey (GLF) for 2007-2009.Results: Smoking prevalence estimates of all the surveys were similar from 2008 onwards (e. g 2008 STS = 22.0%, 95% C. I. = 21.4% to 22.6%, HSE = 21.7%, 95% C. I. = 20.9% to 22.6%, GLF = 20.8%, 95% C. I. = 19.7% to 21.9%), although there was heterogeneity in 2007 (chi-square = 50.30, p < 0.001). Some differences were observed across surveys within sociodemographic sub-groups, although largely in 2007. Cigarette consumption was virtually identical in all surveys and years.Conclusion: There is reason to believe that the STS findings (see http://www.smokinginengland.info) are generalisable to the adult population of England

Adapting to compromised routines: Parental perspectives on physical activity and health for children and adolescents with type 1 diabetes in the UK during COVID-19 lockdown

\ua9 2024 The Author(s)Purpose: To determine how COVID-19 lockdown impacted physical activity (PA) levels, wellbeing, and diabetes management in children (aged 0–17 years) with type 1 diabetes (T1D), from the perspectives of their parent/guardian. Design and methods: This qualitative descriptive study is part of a larger, parallel mixed-methods design study, which incorporated a cross-sectional survey and semi-structured one-to-one interviews. Interviewees were recruited from the survey, which was distributed to parents of children/adolescents with T1D in the UK. Interviews explored diabetes management, mental and physical wellbeing, changes in PA levels, sleep quality before/during lockdown, and the effects of lockdown on the individual and their family. The interviews were transcribed and the data were analysed thematically. Results: 14 interviews were conducted with parents. Thematic analysis generated a central theme of routine disruption, with four further themes on diabetes management routines, harnessing the opportunities of lockdown, weighing up risk, and variable impact on wellbeing. Conclusions: Maintaining or increasing PA during COVID-19 lockdown was associated with better diabetes management, sleep, and wellbeing for children/adolescents with T1D, despite significant disruption to established routines. Use of technology during the pandemic contributed positively to wellbeing. Practice implications: It is crucial to emphasize the significance of maintaining a well-structured routine when treating patients with type 1 diabetes. A consistent routine, incorporating regular physical exercise and good sleep hygiene, will help with managing overall diabetes control

Is a combination of varenicline and nicotine patch more effective in helping smokers quit than varenicline alone? A randomised controlled trial

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Processes and patterns of glacier-influenced sedimentation and recent tidewater glacier dynamics in Darbel Bay, western Antarctic Peninsula

AbstractBathymetric data of unprecedented resolution are used to provide insights into former ice dynamics and glacial processes in a western Antarctic Peninsula embayment. An assemblage of submarine glacial landforms, which includes subglacially produced streamlined features and ice-marginal ridges, reveals the former pattern of ice flow and retreat. A group of more than 250 small (&lt; 1–3 m high, 10–20 m wide) and relatively evenly spaced recessional moraines was identified beyond the margin of Philippa Glacier. The small recessional moraines are interpreted to have been produced during short-lived, possibly annual re-advances of a grounded ice margin during overall retreat. This is the first time that these features have been shown to be part of the assemblage of landforms produced by tidewater glaciers on the Antarctic Peninsula. Glacier-terminus changes during the last four decades, mapped from LANDSAT satellite images, were analysed to determine whether the moraines were produced during recent still-stands or re-advances of Philippa Glacier and to further investigate the short-term (annual to decadal) variability in ice-marginal position in tidewater glacier systems. The asynchronous response of individual tidewater glaciers in Darbel Bay is interpreted to be controlled mainly by local topography rather than by glacier catchment-area size.C.L. Batchelor was in receipt of a Junior Research Fellowship from Newnham College, Cambridge during this work. K.A Hogan and R.D Larter are supported by the Polar Science for Planet Earth programme funded by the Natural Environment Research Council, U.K

The metabolome as a diagnostic for maximal aerobic capacity during exercise in type 1 diabetes

\ua9 The Author(s) 2024.Aims/hypothesis: Our aim was to characterise the in-depth metabolic response to aerobic exercise and the impact of residual pancreatic beta cell function in type 1 diabetes. We also aimed to use the metabolome to distinguish individuals with type 1 diabetes with reduced maximal aerobic capacity in exercise defined by V˙O2peak. Methods: Thirty participants with type 1 diabetes (≥3 years duration) and 30 control participants were recruited. Groups did not differ in age or sex. After quantification of peak stimulated C-peptide, participants were categorised into those with undetectable (&lt;3 pmol/l), low (3–200 pmol/l) or high (&gt;200 pmol/l) residual beta cell function. Maximal aerobic capacity was assessed by V˙O2peak test and did not differ between control and type 1 diabetes groups. All participants completed 45 min of incline treadmill walking (60% V˙O2peak) with venous blood taken prior to exercise, immediately post exercise and after 60 min recovery. Serum was analysed using targeted metabolomics. Metabolomic data were analysed by multivariate statistics to define the metabolic phenotype of exercise in type 1 diabetes. Receiver operating characteristic (ROC) curves were used to identify circulating metabolomic markers of maximal aerobic capacity (V˙O2peak) during exercise in health and type 1 diabetes. Results: Maximal aerobic capacity (V˙O2peak) inversely correlated with HbA1c in the type 1 diabetes group (r2=0.17, p=0.024). Higher resting serum tricarboxylic acid cycle metabolites malic acid (fold change 1.4, p=0.001) and lactate (fold change 1.22, p=1.23 710−5) differentiated people with type 1 diabetes. Higher serum acylcarnitines (AC) (AC C14:1, F value=12.25, p=0.001345; AC C12, F value=11.055, p=0.0018) were unique to the metabolic response to exercise in people with type 1 diabetes. C-peptide status differentially affected metabolic responses in serum ACs during exercise (AC C18:1, leverage 0.066; squared prediction error 3.07). The malic acid/pyruvate ratio in rested serum was diagnostic for maximal aerobic capacity (V˙O2peak) in people with type 1 diabetes (ROC curve AUC 0.867 [95% CI 0.716, 0.956]). Conclusions/interpretation: The serum metabolome distinguishes high and low maximal aerobic capacity and has diagnostic potential for facilitating personalised medicine approaches to manage aerobic exercise and fitness in type 1 diabetes. Graphical Abstract: (Figure presented.)

FSL-BM: Fuzzy Supervised Learning with Binary Meta-Feature for Classification

This paper introduces a novel real-time Fuzzy Supervised Learning with Binary Meta-Feature (FSL-BM) for big data classification task. The study of real-time algorithms addresses several major concerns, which are namely: accuracy, memory consumption, and ability to stretch assumptions and time complexity. Attaining a fast computational model providing fuzzy logic and supervised learning is one of the main challenges in the machine learning. In this research paper, we present FSL-BM algorithm as an efficient solution of supervised learning with fuzzy logic processing using binary meta-feature representation using Hamming Distance and Hash function to relax assumptions. While many studies focused on reducing time complexity and increasing accuracy during the last decade, the novel contribution of this proposed solution comes through integration of Hamming Distance, Hash function, binary meta-features, binary classification to provide real time supervised method. Hash Tables (HT) component gives a fast access to existing indices; and therefore, the generation of new indices in a constant time complexity, which supersedes existing fuzzy supervised algorithms with better or comparable results. To summarize, the main contribution of this technique for real-time Fuzzy Supervised Learning is to represent hypothesis through binary input as meta-feature space and creating the Fuzzy Supervised Hash table to train and validate model.Comment: FICC201

Rapid reduction versus abrupt quitting for smokers who want to stop soon: a randomised controlled non-inferiority trial

Background: The standard way to stop smoking is to stop abruptly on a quit day with no prior reduction in consumption of cigarettes. Many smokers feel that reduction is natural and if reduction programmes were offered, many more might take up treatment. Few trials of reduction versus abrupt cessation have been completed. Most are small, do not use pharmacotherapy, and do not meet the standards necessary to obtain a marketing authorisation for a pharmacotherapy.\ud Design/Methods: We will conduct a non-inferiority andomised trial of rapid reduction versus standard abrupt cessation among smokers who want to stop smoking. In the reduction arm,participants will be advised to reduce smoking consumption by half in the first week and to 25% of baseline in the second, leading up to a quit day at which participants will stop smoking completely.This will be assisted by nicotine patches and an acute form of nicotine replacement therapy. In the abrupt arm participants will use nicotine patches only, whilst smoking as normal, for two weeks prior to a quit day, at which they will also stop smoking completely. Smokers in either arm will have standard withdrawal orientated behavioural support programme with a combination of nicotine patches and acute nicotine replacement therapy post-cessation.\ud Outcomes/Follow-up: The primary outcome of interest will be prolonged abstinence from smoking, with secondary trial outcomes of point prevalence, urges to smoke and withdrawal\ud symptoms. Follow up will take place at 4 weeks, 8 weeks and 6 months post-quit day

A simulation study of diagnostics for bias in non-probability samples

A non-probability sampling mechanism is likely to bias estimates of parameters with respect to a target population of interest. This bias poses a unique challenge when selection is \u27non-ignorable\u27, i.e. dependent upon the unobserved outcome of interest, since it is then undetectable and thus cannot be ameliorated. We extend a simulation study by Nishimura et al. [International Statistical Review, 84, 43--62 (2016)], adding a recently published statistic, the so-called \u27standardized measure of unadjusted bias\u27, which explicitly quantifies the extent of bias under the assumption that a specified amount of non-ignorable selection exists. Our findings suggest that this new sensitivity diagnostic is considerably correlated with, and more predictive of, the true, unknown extent of selection bias than other diagnostics, even when the underlying assumed level of non-ignorability is incorrect