Interactive processes link the multiple symptoms of fatigue in sport competition

Muscle physiologists often describe fatigue simply as a decline of muscle force and infer this causes an athlete to slow down. In contrast, exercise scientists describe fatigue during sport competition more holistically as an exercise-induced impairment of performance. The aim of this review is to reconcile the different views by evaluating the many performance symptoms/measures and mechanisms of fatigue. We describe how fatigue is assessed with muscle, exercise or competition performance measures. Muscle performance (single muscle test measures) declines due to peripheral fatigue (reduced muscle cell force) and/or central fatigue (reduced motor drive from the CNS). Peak muscle force seldom falls by >30% during sport but is often exacerbated during electrical stimulation and laboratory exercise tasks. Exercise performance (whole-body exercise test measures) reveals impaired physical/technical abilities and subjective fatigue sensations. Exercise intensity is initially sustained by recruitment of new motor units and help from synergistic muscles before it declines. Technique/motor skill execution deviates as exercise proceeds to maintain outcomes before they deteriorate, e.g. reduced accuracy or velocity. The sensation of fatigue incorporates an elevated rating of perceived exertion (RPE) during submaximal tasks, due to a combination of peripheral and higher CNS inputs. Competition performance (sport symptoms) is affected more by decision-making and psychological aspects, since there are opponents and a greater importance on the result. Laboratory based decision making is generally faster or unimpaired. Motivation, self-efficacy and anxiety can change during exercise to modify RPE and, hence, alter physical performance. Symptoms of fatigue during racing, team-game or racquet sports are largely anecdotal, but sometimes assessed with time-motion analysis. Fatigue during brief all-out racing is described biomechanically as a decline of peak velocity, along with altered kinematic components. Longer sport events involve pacing strategies, central and peripheral fatigue contributions and elevated RPE. During match play, the work rate can decline late in a match (or tournament) and/or transiently after intense exercise bursts. Repeated sprint ability, agility and leg strength become slightly impaired. Technique outcomes, such as velocity and accuracy for throwing, passing, hitting and kicking, can deteriorate. Physical and subjective changes are both less severe in real rather than simulated sport activities. Little objective evidence exists to support exercise-induced mental lapses during sport. A model depicting mind-body interactions during sport competition shows that the RPE centre-motor cortex-working muscle sequence drives overall performance levels and, hence, fatigue symptoms. The sporting outputs from this sequence can be modulated by interactions with muscle afferent and circulatory feedback, psychological and decision-making inputs. Importantly, compensatory processes exist at many levels to protect against performance decrements. Small changes of putative fatigue factors can also be protective. We show that individual fatigue factors including diminished carbohydrate availability, elevated serotonin, hypoxia, acidosis, hyperkalaemia, hyperthermia, dehydration and reactive oxygen species, each contribute to several fatigue symptoms. Thus, multiple symptoms of fatigue can occur simultaneously and the underlying mechanisms overlap and interact. Based on this understanding, we reinforce the proposal that fatigue is best described globally as an exercise-induced decline of performance as this is inclusive of all viewpoints.

Chronological age and age-related cognitive deficits are associated with an increase in multiple types of driving errors in late life

Objective: Older driver research has mostly focused on identifying that small proportion of older drivers who are unsafe. Little is known about how normal cognitive changes in aging affect driving in the wider population of adults who drive regularly. We evaluated the association of cognitive function and age, with driving errors. Method: A sample of 266 drivers aged 70 to 88 years were assessed on abilities that decline in normal aging (visual attention, processing speed, inhibition, reaction time, task switching) and the UFOV® which is a validated screening instrument for older drivers. Participants completed an on-road driving test. Generalized linear models were used to estimate the associations of cognitive factor with specific driving errors and number of errors in self-directed and instructor navigated conditions. Results: All errors types increased with chronological age. Reaction time was not associated with driving errors in multivariate analyses. A cognitive factor measuring Speeded Selective Attention and Switching was uniquely associated with the most errors types. The UFOV predicted blindspot errors and errors on dual carriageways. After adjusting for age, education and gender the cognitive factors explained 7% of variance in the total number of errors in the instructor navigated condition and 4% of variance in the self-navigated condition. Conclusion: We conclude that among older drivers errors increase with age and are associated with speeded selective attention particularly when that requires attending to the stimuli in the periphery of the visual field, task switching, errors inhibiting responses and visual discrimination. These abilities should be the target of cognitive training.

Multiple perspectives on engaging future engineers

Engaging future engineers is a central topic in everyday conversations on engineering education. Considerable investments have been made to make engineering more engaging, recruit and retain aspiring engineers, and to design an education to prepare future engineers. However, the impact of these efforts has been less than intended. It is imperative that the community reflects on progress and sets a more effective path for the future.

Evidence for CRHR1 in multiple sclerosis using supervised machine learning and meta-analysis in 12 566 individuals

The primary genetic risk factor in multiple sclerosis (MS) is the HLA-DRB1*1501 allele; however, much of the remaining genetic contribution to MS has yet to be elucidated. Several lines of evidence support a role for neuroendocrine system involvement in autoimmunity which may, in part, be genetically determined. Here, we comprehensively investigated variation within eight candidate hypothalamic-pituitary-adrenal (HPA) axis genes and susceptibility to MS. A total of 326 SNPs were investigated in a discovery dataset of 1343 MS cases and 1379 healthy controls of European ancestry using a multi-analytical strategy. Random Forests, a supervised machine-learning algorithm, identified eight intronic SNPs within the corticotrophin-releasing hormone receptor 1 or CRHR1 locus on 17q21.31 as important predictors of MS. On the basis of univariate analyses, six CRHR1 variants were associated with decreased risk for disease following a conservative correction for multiple tests. Independent replication was observed for CRHR1 in a large meta-analysis comprising 2624 MS cases and 7220 healthy controls of European ancestry. Results from a combined meta-analysis of all 3967 MS cases and 8599 controls provide strong evidence for the involvement of CRHR1 in MS. The strongest association was observed for rs242936 (OR = 0.82, 95% CI = 0.74-0.90, P = 9.7 × 10-5). Replicated CRHR1 variants appear to exist on a single associated haplotype. Further investigation of mechanisms involved in HPA axis regulation and response to stress in MS pathogenesis is warranted. © The Author 2010. Published by Oxford University Press. All rights reserved.

Investigating the performance of automatic new topic identification across multiple datasets 1

Recent studies on automatic new topic identification in Web search engine user sessions demonstrated that neural networks are successful in automatic new topic identification. However most of this work applied their new topic identification algorithms on data logs from a single search engine. In this study, we investigate whether the application of neural networks for automatic new topic identification are more successful on some search engines than others. Sample data logs from the Norwegian search engine FAST (currently owned by Overture) and Excite are used in this study. Findings of this study suggest that query logs with more topic shifts tend to provide more successful results on shift-based performance measures, whereas logs with more topic continuations tend to provide better results on continuation-based performance measures.

Towards automatic object segmentation with sequential multiple views

Object segmentation is one of the fundamental steps for a number of robotic applications such as manipulation, object detection, and obstacle avoidance. This paper proposes a visual method for incorporating colour and depth information from sequential multiview stereo images to segment objects of interest from complex and cluttered environments. Rather than segmenting objects using information from a single frame in the sequence, we incorporate information from neighbouring views to increase the reliability of the information and improve the overall segmentation result. Specifically, dense depth information of a scene is computed using multiple view stereo. Depths from neighbouring views are reprojected into the reference frame to be segmented compensating for imperfect depth computations for individual frames. The multiple depth layers are then combined with color information from the reference frame to create a Markov random field to model the segmentation problem. Finally, graphcut optimisation is employed to infer pixels belonging to the object to be segmented. The segmentation accuracy is evaluated over images from an outdoor video sequence demonstrating the viability for automatic object segmentation for mobile robots using monocular cameras as a primary sensor.

Analysis of multiple shared channel cooperative routing in OFDM based wireless networks

Diversity techniques have long been used to combat the channel fading in wireless communications systems. Recently cooperative communications has attracted lot of attention due to many benefits it offers. Thus cooperative routing protocols with diversity transmission can be developed to exploit the random nature of the wireless channels to improve the network efficiency by selecting multiple cooperative nodes to forward data. In this paper we analyze and evaluate the performance of a novel routing protocol with multiple cooperative nodes which share multiple channels. Multiple shared channels cooperative (MSCC) routing protocol achieves diversity advantage by using cooperative transmission. It unites clustering hierarchy with a bandwidth reuse scheme to mitigate the co-channel interference. Theoretical analysis of average packet reception rate and network throughput of the MSCC protocol are presented and compared with simulated results.

Evaluation of novel Streptococcus pyogenes vaccine candidates incorporating multiple conserved sequences from the C-repeat region of the M-protein

A major challenge for Streptococcus pyogenes vaccine development is the identification of epitopes that confer protection from infection by multiple S. pyogenes M-types. Here we have identified and characterised the distribution of common variant sequences from individual repeat units of the C-repeat region (CRR) of M-proteins representing 77 different M-types. Three polyvalent fusion vaccine candidates (SV1, SV2 and SV3) incorporating the most common variants were subsequently expressed and purified, and demonstrated to be alpha-helical by Circular Dichroism (CD), a secondary conformational characteristic of the CRR in the M-protein. Antibodies raised against each of these constructs recognise M-proteins that vary in their CRR, and bind to the surface of multiple S. pyogenes isolates. Antibodies raised against SV1, containing five variant sequences, also kill heterologous S. pyogenes isolates in in vitro bactericidal assays. Further structural characterisation of this construct demonstrated the conformation of SV1 was stable at different pHs, and thermal unfolding of SV1 a reversible process. Our findings demonstrate that linkage of multiple variant sequences into a single recombinant construct overcomes the need to embed the variant sequences in foreign helix promoting flanking sequences for conformational stability, and demonstrates the viability of the polyvalent candidates as global S. pyogenes vaccine candidates.

Multiple perspectives of design thinking in business education

Business education leaders have expressed interest in learning more about design and design thinking and their contributions to better problem framing, problem solving and to generating new solutions. Many business schools have engaged in educational programs with students from multiple disciplines, applying design thinking to business problems around workplace issues. This paper investigates a range of educational programs that teach design thinking to students in business education, at undergraduate and postgraduate levels around the world. We identify four patterns of program delivery that are emerging: human-centered design, integrative thinking, design management and design as strategy and discuss contributions from each. We expect that these four patterns of program delivery will continue and predict an increasing focus on programs around design as strategy in the near future.

Reduced variance in monozygous twins for multiple MR parameters : implications for disease studies and the genetic basis of brain structure

Twin studies offer the opportunity to determine the relative contribution of genes versus environment in traits of interest. Here, we investigate the extent to which variance in brain structure is reduced in monozygous twins with identical genetic make-up. We investigate whether using twins as compared to a control population reduces variability in a number of common magnetic resonance (MR) structural measures, and we investigate the location of areas under major genetic influences. This is fundamental to understanding the benefit of using twins in studies where structure is the phenotype of interest. Twenty-three pairs of healthy MZ twins were compared to matched control pairs. Volume, T2 and diffusion MR imaging were performed as well as spectroscopy (MRS). Images were compared using (i) global measures of standard deviation and effect size, (ii) voxel-based analysis of similarity and (iii) intra-pair correlation. Global measures indicated a consistent increase in structural similarity in twins. The voxel-based and correlation analyses indicated a widespread pattern of increased similarity in twin pairs, particularly in frontal and temporal regions. The areas of increased similarity were most widespread for the diffusion trace and least widespread for T2. MRS showed consistent reduction in metabolite variation that was significant in the temporal lobe N-acetylaspartate (NAA). This study has shown the distribution and magnitude of reduced variability in brain volume, diffusion, T2 and metabolites in twins. The data suggest that evaluation of twins discordant for disease is indeed a valid way to attribute genetic or environmental influences to observed abnormalities in patients since evidence is provided for the underlying assumption of decreased variability in twins.

The role of the multiple banded antigen of ureaplasma parvum in intra-amniotic infection : major virulence factor or decoy?

The multiple banded antigen (MBA) is a predicted virulence factor of Ureaplasma species. Antigenic variation of the MBA is a potential mechanism by which ureaplasmas avoid immune recognition and cause chronic infections of the upper genital tract of pregnant women. We tested whether the MBA is involved in the pathogenesis of intra-amniotic infection and chorioamnionitis by injecting virulent or avirulent-derived ureaplasma clones (expressing single MBA variants) into the amniotic fluid of pregnant sheep. At 55 days of gestation pregnant ewes (n = 20) received intra-amniotic injections of virulent-derived or avirulent-derived U. parvum serovar 6 strains (2×104 CFU), or 10B medium (n = 5). Amniotic fluid was collected every two weeks post-infection and fetal tissues were collected at the time of surgical delivery of the fetus (140 days of gestation). Whilst chronic colonisation was established in the amniotic fluid of animals infected with avirulent-derived and virulent-derived ureaplasmas, the severity of chorioamnionitis and fetal inflammation was not different between these groups (p>0.05). MBA size variants (32–170 kDa) were generated in vivo in amniotic fluid samples from both the avirulent and virulent groups, whereas in vitro antibody selection experiments led to the emergence of MBA-negative escape variants in both strains. Anti-ureaplasma IgG antibodies were detected in the maternal serum of animals from the avirulent (40%) and virulent (55%) groups, and these antibodies correlated with increased IL-1β, IL-6 and IL-8 expression in chorioamnion tissue (p<0.05). We demonstrate that ureaplasmas are capable of MBA phase variation in vitro; however, ureaplasmas undergo MBA size variation in vivo, to potentially prevent eradication by the immune response. Size variation of the MBA did not correlate with the severity of chorioamnionitis. Nonetheless, the correlation between a maternal humoral response and the expression of chorioamnion cytokines is a novel finding. This host response may be important in the pathogenesis of inflammation-mediated adverse pregnancy outcomes.

Book review : "Carbon Capture and Storage Emerging Legal and Regulatory Issues" edited by Ian Havercroft, Richard Macrory, Richard B Stewart, Oxford, Hart Publishing, 2011

As the international community struggles to find a cost-effective solution to mitigate climate change and reduce greenhouse gas emissions, carbon capture and storage (CCS) has emerged as a project mechanism with the potential to assist in transitioning society towards its low carbon future. Being a politically attractive option, legal regimes to promote and approve CCS have proceeded at an accelerated pace in multiple jurisdictions including the European Union and Australia. This acceleration and emphasis on the swift commercial deployment of CCS projects has left the legal community in the undesirable position of having to advise on the strengths and weaknesses of the key features of these regimes once they have been passed and become operational. This is an area where environmental law principles are tested to their very limit. On the one hand, implementation of this new technology should proceed in a precautionary manner to avoid adverse impacts on the atmosphere, local community and broader environment. On the other hand, excessive regulatory restrictions will stifle innovation and act as a barrier to the swift deployment of CCS projects around the world. Finding the balance between precaution and innovation is no easy feat. This is an area where lawyers, academics, regulators and industry representatives can benefit from the sharing of collective experiences, both positive and negative, across the jurisdictions. This exemplary book appears to have been collated with this philosophy in mind and provides an insightful addition to the global dialogue on establishing effective national and international regimes for the implementation of CCS projects...

Handling incomplete data in survival analysis with multiple covariates

This paper studies the missing covariate problem which is often encountered in survival analysis. Three covariate imputation methods are employed in the study, and the effectiveness of each method is evaluated within the hazard prediction framework. Data from a typical engineering asset is used in the case study. Covariate values in some time steps are deliberately discarded to generate an incomplete covariate set. It is found that although the mean imputation method is simpler than others for solving missing covariate problems, the results calculated by it can differ largely from the real values of the missing covariates. This study also shows that in general, results obtained from the regression method are more accurate than those of the mean imputation method but at the cost of a higher computational expensive. Gaussian Mixture Model (GMM) method is found to be the most effective method within these three in terms of both computation efficiency and predication accuracy.

Information sharing in Onesocialweb using a multiple profile manager to better informed medical decision making processes

The study shows an alternative solution to existing efforts at solving the problem of how to centrally manage and synchronise users’ Multiple Profiles (MP) across multiple discrete social networks. Most social network users hold more than one social network account and utilise them in different ways depending on the digital context (Iannella, 2009a). They may, for example, enjoy friendly chat on Facebook1, professional discussion on LinkedIn2, and health information exchange on PatientsLikeMe3 In this thesis the researcher proposes a framework for the management of a user’s multiple online social network profiles. A demonstrator, called Multiple Profile Manager (MPM), will be showcased to illustrate how effective the framework will be. The MPM will achieve the required profile management and synchronisation using a free, open, decentralized social networking platform (OSW) that was proposed by the Vodafone Group in 2010. The proposed MPM will enable a user to create and manage an integrated profile (IP) and share/synchronise this profile with all their social networks. The necessary protocols to support the prototype are also proposed by the researcher. The MPM protocol specification defines an Extensible Messaging and Presence Protocol (XMPP) extension for sharing vCard and social network accounts information between the MPM Server, MPM Client, and social network sites (SNSs). . Therefore many web users need to manage disparate profiles across many distributed online sources. Maintaining these profiles is cumbersome, time-consuming, inefficient, and may lead to lost opportunity. The writer of this thesis adopted a research approach and a number of use cases for the implementation of the project. The use cases were created to capture the functional requirements of the MPM and to describe the interactions between users and the MPM. In the research a development process was followed in establishing the prototype and related protocols. The use cases were subsequently used to illustrate the prototype via the screenshots taken of the MPM client interfaces. The use cases also played a role in evaluating the outcomes of the research such as the framework, prototype, and the related protocols. An innovative application of this project is in the area of public health informatics. The researcher utilised the prototype to examine how the framework might benefit patients and physicians. The framework can greatly enhance health information management for patients and more importantly offer a more comprehensive personal health overview of patients to physicians. This will give a more complete picture of the patient’s background than is currently available and will prove helpful in providing the right treatment. The MPM prototype and related protocols have a high application value as they can be integrated into the real OSW platform and so serve users in the modern digital world. They also provide online users with a real platform for centrally storing their complete profile data, efficiently managing their personal information, and moreover, synchronising the overall complete profile with each of their discrete profiles stored in their different social network sites.

Challenges in the context-aware management of business processes : a multiple case study

Current conceptualizations of organizational processes consider them as internally optimized yet static systems. Still, turbulences in the contextual environment of a firm often lead to adaptation requirements that these processes are unable to fulfil. Based on a multiple case study of the core processes of two large organizations, we offer an extended conceptualisation of business processes as complex adaptive systems. This conceptualization can enable firms to optimise business processes by analysing operations in different contexts and by examining the complex interaction between external, contextual elements and internal agent schemata. From this analysis, we discuss how information technology can play a vital goal in achieving this goal by providing discovery, analysis, and automation support. We detail implications for research and practice.