A comparison of training methods to increase neck muscle strength

Objective To compare two neck strength training modalities. Background Neck injury in pilots flying high performance aircraft is a concern in aviation medicine. Strength training may be an effective means to strengthen the neck and decrease injury risk. Methods The cohort consisted of 32 age-height-weight matched participants, divided into two experimental groups; the Multi-Cervical Unit (MCU) and Thera-Band tubing groups (THER), and a control (CTRL) group. Ten weeks of training were undertaken and pre-and post isometric strength testing for all groups was performed on the MCU. Comparisons between the three groups were made using a Kruskal-Wallis test and effect sizes between the MCU and the THER groups and the THER and CTRL groups were also calculated. Results The MCU group displayed the greatest increase in isometric strength (flexion 64.4%, extension 62.9%, left lateral flexion 53.3%, right lateral flexion 49.1%) and differences were only statistically significant (p<0.05) when compared to the CTRL group. Increases in neck strength for the THER group were lower than that shown in the MCU group (flexion 42.0%, extension 29.9%, left lateral flexion 26.7%, right lateral flexion 24.1%). Moderate to large effect sizes were found between the MCU and THER as well as the THER and CTRL groups. Conclusions This study demonstrated that the MCU was the most effective training modality to increase isometric cervical muscle strength. Thera-Band tubing did however, produce moderate gains in isometric neck strength

Comparison of decision tree, support vector machines, and Bayesian network approaches for classification of falls in Parkinson’s disease

Being able to accurately predict the risk of falling is crucial in patients with Parkinson’s dis- ease (PD). This is due to the unfavorable effect of falls, which can lower the quality of life as well as directly impact on survival. Three methods considered for predicting falls are decision trees (DT), Bayesian networks (BN), and support vector machines (SVM). Data on a 1-year prospective study conducted at IHBI, Australia, for 51 people with PD are used. Data processing are conducted using rpart and e1071 packages in R for DT and SVM, con- secutively; and Bayes Server 5.5 for the BN. The results show that BN and SVM produce consistently higher accuracy over the 12 months evaluation time points (average sensitivity and specificity > 92%) than DT (average sensitivity 88%, average specificity 72%). DT is prone to imbalanced data so needs to adjust for the misclassification cost. However, DT provides a straightforward, interpretable result and thus is appealing for helping to identify important items related to falls and to generate fallers’ profiles.

The Google Online Marketing Challenge: A Transnational Comparison of Classroom Learning with Real Clients, Real Money, and Real Advertising Campaigns

In 2008, a collaborative partnership between Google and academia launched the Google Online Marketing Challenge (hereinafter Google Challenge), perhaps the world’s largest in-class competition for higher education students. In just two years, almost 20,000 students from 58 countries participated in the Google Challenge. The Challenge gives undergraduate and graduate students hands-on experience with the world’s fastest growing advertising mechanism, search engine advertising. Funded by Google, students develop an advertising campaign for a small to medium sized enterprise and manage the campaign over three consecutive weeks using the Google AdWords platform. This article explores the Challenge as an innovative pedagogical tool for marketing educators. Based on the experiences of three instructors in Australia, Canada and the United States, this case study discusses the opportunities and challenges of integrating this dynamic problem-based learning approach into the classroom.

Personality, health and lifestyle in a questionnaire family study: A comparison between highly cooperative and less cooperative families

The effect of nonresponse on health and lifestyle measures has received extensive study, showing at most relatively modest effects. Nonresponse bias with respect to personality has been less thoroughly investigated. The present study uses data from responding individuals as a proxy for the missing data of their nonresponding family members to examine the presence of nonresponse bias for personality traits and disorders as well as health and lifestyle traits. We looked at the Big Five personality traits, borderline personality disorder (BPD) features, attention-deficit/hyperactivity disorder, Anger, and several measures of health (Body Mass Index, migraine) and lifestyle (smoking, alcohol use). In general, outcomes tend to be slightly more favorable for individuals from highly cooperative families compared to individuals from less cooperative families. The only significant difference was found for BPD features (p = .001). However, the absolute difference in mean scores is very small, less than 1 point for a scale ranging from 0 to 72. In conclusion, survey data on personality, health and lifestyle are relatively unbiased with respect to nonresponse.

A comparison of DNA pools constructed following whole genome amplification for two-stage SNP genotyping designs

Genotyping in DNA pools reduces the cost and the time required to complete large genotyping projects. The aim of the present study was to evaluate pooling as part of a strategy for fine mapping in regions of significant linkage. Thirty-nine single nucleotide polymorphisms (SNPs) were analyzed in two genomic DNA pools of 384 individuals each and results compared with data after typing all individuals used in the pools. There were no significant differences using data from either 2 or 8 heterozygous individuals to correct frequency estimates for unequal allelic amplification. After correction, the mean difference between estimates from the genomic pool and individual allele frequencies was .033. A major limitation of the use of DNA pools is the time and effort required to carefully adjust the concentration of each individual DNA sample before mixing aliquots. Pools were also constructed by combining DNA after Multiple Displacement Amplification (MDA). The MDA pools gave similar results to pools constructed after careful DNA quantitation (mean difference from individual genotyping .040) and MDA provides a rapid method to generate pools suitable for some applications. Pools provide a rapid and cost-effective screen to eliminate SNPs that are not polymorphic in a test population and can detect minor allele frequencies as low as 1% in the pooled samples. With current levels of accuracy, pooling is best suited to an initial screen in the SNP validation process that can provide high-throughput comparisons between cases and controls to prioritize SNPs for subsequent individual genotyping.

Multi-species sequence comparison reveals conservation of ghrelin gene-derived splice variants encoding a truncated ghrelin peptide

The peptide hormone ghrelin is a potent orexigen produced predominantly in the stomach. It has a number of other biological actions, including roles in appetite stimulation, energy balance, the stimulation of growth hormone release and the regulation of cell proliferation. Recently, several ghrelin gene splice variants have been described. Here, we attempted to identify conserved alternative splicing of the ghrelin gene by cross-species sequence comparisons. We identified a novel human exon 2-deleted variant and provide preliminary evidence that this splice variant and in1-ghrelin encode a C-terminally truncated form of the ghrelin peptide, termed minighrelin. These variants are expressed in humans and mice, demonstrating conservation of alternative splicing spanning 90 million years. Minighrelin appears to have similar actions to full-length ghrelin, as treatment with exogenous minighrelin peptide stimulates appetite and feeding in mice. Forced expression of the exon 2-deleted preproghrelin variant mirrors the effect of the canonical preproghrelin, stimulating cell proliferation and migration in the PC3 prostate cancer cell line. This is the first study to characterise an exon 2-deleted preproghrelin variant and to demonstrate sequence conservation of ghrelin gene-derived splice variants that encode a truncated ghrelin peptide. This adds further impetus for studies into the alternative splicing of the ghrelin gene and the function of novel ghrelin peptides in vertebrates.

A comparison of self-nominated and actual speeds in work zones

Despite significant research on drivers’ speeding behavior in work zones, little is known about how well drivers’ judgments of appropriate speeds match their actual speeds and what factors influence their judgments. This study aims to fill these two important gaps in the literature by comparing observed speeds in two work zones with drivers’ self-nominated speeds for the same work zones. In an online survey, drivers nominated speeds for the two work zones based on photographs in which the actual posted speed limits were not revealed. A simultaneous equation modelling approach was employed to examine the effects of driver characteristics on their self-nominated speeds. The results showed that survey participants nominated lower speeds (corresponding to higher compliance rates) than those which were observed. Higher speeds were nominated by males than females, young and middle aged drivers than older drivers, and drivers with truck driving experience than those who drive only cars. Larger differences between nominated and observed speeds were found among car drivers than truck drivers. These differences suggest that self-nominated speeds might not be valid indicators of the observed work zone speeds and therefore should not be used as an alternative to observed speed data.

Comparison of treatment effect sizes associated with surrogate and final patient relevant outcomes in randomised controlled trials: meta-epidemiological study

Objective To quantify and compare the treatment effect and risk of bias of trials reporting biomarkers or intermediate outcomes (surrogate outcomes) versus trials using final patient relevant primary outcomes. Design Meta-epidemiological study. Data sources All randomised clinical trials published in 2005 and 2006 in six high impact medical journals: Annals of Internal Medicine, BMJ, Journal of the American Medical Association, Lancet, New England Journal of Medicine, and PLoS Medicine. Study selection Two independent reviewers selected trials. Data extraction Trial characteristics, risk of bias, and outcomes were recorded according to a predefined form. Two reviewers independently checked data extraction. The ratio of odds ratios was used to quantify the degree of difference in treatment effects between the trials using surrogate outcomes and those using patient relevant outcomes, also adjusted for trial characteristics. A ratio of odds ratios >1.0 implies that trials with surrogate outcomes report larger intervention effects than trials with patient relevant outcomes. Results 84 trials using surrogate outcomes and 101 using patient relevant outcomes were considered for analyses. Study characteristics of trials using surrogate outcomes and those using patient relevant outcomes were well balanced, except for median sample size (371 v 741) and single centre status (23% v 9%). Their risk of bias did not differ. Primary analysis showed trials reporting surrogate endpoints to have larger treatment effects (odds ratio 0.51, 95% confidence interval 0.42 to 0.60) than trials reporting patient relevant outcomes (0.76, 0.70 to 0.82), with an unadjusted ratio of odds ratios of 1.47 (1.07 to 2.01) and adjusted ratio of odds ratios of 1.46 (1.05 to 2.04). This result was consistent across sensitivity and secondary analyses. Conclusions Trials reporting surrogate primary outcomes are more likely to report larger treatment effects than trials reporting final patient relevant primary outcomes. This finding was not explained by differences in the risk of bias or characteristics of the two groups of trials.

Survival analysis of time-to-event data in respiratory health research studies

This article provides a review of techniques for the analysis of survival data arising from respiratory health studies. Popular techniques such as the Kaplan–Meier survival plot and the Cox proportional hazards model are presented and illustrated using data from a lung cancer study. Advanced issues are also discussed, including parametric proportional hazards models, accelerated failure time models, time-varying explanatory variables, simultaneous analysis of multiple types of outcome events and the restricted mean survival time, a novel measure of the effect of treatment.

Data distribution and task scheduling for distributed computing of all-to-all comparison problems

This research studied distributed computing of all-to-all comparison problems with big data sets. The thesis formalised the problem, and developed a high-performance and scalable computing framework with a programming model, data distribution strategies and task scheduling policies to solve the problem. The study considered storage usage, data locality and load balancing for performance improvement in solving the problem. The research outcomes can be applied in bioinformatics, biometrics and data mining and other domains in which all-to-all comparisons are a typical computing pattern.

Using a glow graph to represent data flow and dependency in event logs

The idea of extracting knowledge in process mining is a descendant of data mining. Both mining disciplines emphasise data flow and relations among elements in the data. Unfortunately, challenges have been encountered when working with the data flow and relations. One of the challenges is that the representation of the data flow between a pair of elements or tasks is insufficiently simplified and formulated, as it considers only a one-to-one data flow relation. In this paper, we discuss how the effectiveness of knowledge representation can be extended in both disciplines. To this end, we introduce a new representation of the data flow and dependency formulation using a flow graph. The flow graph solves the issue of the insufficiency of presenting other relation types, such as many-to-one and one-to-many relations. As an experiment, a new evaluation framework is applied to the Teleclaim process in order to show how this method can provide us with more precise results when compared with other representations.

Fluid States: Performances of Unknowing - The LOG

The LOG is the online edited proceedings of PSi#21 Fluid States: Performances of Unknowing, a festival-style series of conferences, symposia and performances across Asia, Africa, Europe, the Pacific and the Americas throughout 2015, incorporating texts, images, videos and other correspondence and commentary from literally hundreds of the world's top drama, theatre, performance and cultural studies scholars.

When and why threats go undetected: Impacts of event rate and shift length on threat detection accuracy during airport baggage screening

Objective: We aimed to assess the impact of task demands and individual characteristics on threat detection in baggage screeners. Background: Airport security staff work under time constraints to ensure optimal threat detection. Understanding the impact of individual characteristics and task demands on performance is vital to ensure accurate threat detection. Method: We examined threat detection in baggage screeners as a function of event rate (i.e., number of bags per minute) and time on task across 4 months. We measured performance in terms of the accuracy of detection of Fictitious Threat Items (FTIs) randomly superimposed on X-ray images of real passenger bags. Results: Analyses of the percentage of correct FTI identifications (hits) show that longer shifts with high baggage throughput result in worse threat detection. Importantly, these significant performance decrements emerge within the first 10 min of these busy screening shifts only. Conclusion: Longer shift lengths, especially when combined with high baggage throughput, increase the likelihood that threats go undetected. Application: Shorter shift rotations, although perhaps difficult to implement during busy screening periods, would ensure more consistently high vigilance in baggage screeners and, therefore, optimal threat detection and passenger safety.

Interdependence between Greece and other European stock markets: A comparison of wavelet and VMD copula, and the portfolio implications

The interdependence of Greece and other European stock markets and the subsequent portfolio implications are examined in wavelet and variational mode decomposition domain. In applying the decomposition techniques, we analyze the structural properties of data and distinguish between short and long term dynamics of stock market returns. First, the GARCH-type models are fitted to obtain the standardized residuals. Next, different copula functions are evaluated, and based on the conventional information criteria and time varying parameter, Joe-Clayton copula is chosen to model the tail dependence between the stock markets. The short-run lower tail dependence time paths show a sudden increase in comovement during the global financial crises. The results of the long-run dependence suggest that European stock markets have higher interdependence with Greece stock market. Individual country’s Value at Risk (VaR) separates the countries into two distinct groups. Finally, the two-asset portfolio VaR measures provide potential markets for Greece stock market investment diversification.

Data-aware task scheduling for all-to-all comparison problems in heterogeneous distributed systems

Solving large-scale all-to-all comparison problems using distributed computing is increasingly significant for various applications. Previous efforts to implement distributed all-to-all comparison frameworks have treated the two phases of data distribution and comparison task scheduling separately. This leads to high storage demands as well as poor data locality for the comparison tasks, thus creating a need to redistribute the data at runtime. Furthermore, most previous methods have been developed for homogeneous computing environments, so their overall performance is degraded even further when they are used in heterogeneous distributed systems. To tackle these challenges, this paper presents a data-aware task scheduling approach for solving all-to-all comparison problems in heterogeneous distributed systems. The approach formulates the requirements for data distribution and comparison task scheduling simultaneously as a constrained optimization problem. Then, metaheuristic data pre-scheduling and dynamic task scheduling strategies are developed along with an algorithmic implementation to solve the problem. The approach provides perfect data locality for all comparison tasks, avoiding rearrangement of data at runtime. It achieves load balancing among heterogeneous computing nodes, thus enhancing the overall computation time. It also reduces data storage requirements across the network. The effectiveness of the approach is demonstrated through experimental studies.