Recovery of Injured Giant Barrel Sponges, Xestospongia muta, Offshore Southeast Florida

Giant barrel sponges, Xestospongia muta, are abundant and important components of the southeast Florida reef system, and are frequently injured from anthropogenic and natural disturbances. There is limited information on the capacity of X. muta to recover from injury and on methods to reattach X. muta fragments. In late 2002, hundreds of barrel sponges offshore southeast Florida (Broward County) were accidentally injured during an authorized dredging operation. In early 2003, two to three months post-injury, 93% of 656 assessed injured sponges appeared to be recovering. In 2006, three years post-injury, nearly 90% of 114 monitored sponges continued to show signs of recovery. Growth rates were estimated by measuring sponge height above visual injury scars and ranged from 0.7 cm yr- ¹ to 6.0 cm yr- ¹. Information on the artificially reattached fragments is limited but did show that X. muta fragments can reattach. This study provides evidence that X. muta in southeast Florida can naturally recover. Details on sponge size class associated recovery processes and growth were not collected due to event associated legal issues limiting the study. Studies to determine detailed growth rates and recovery success for different injury and restoration scenarios will further facilitate restoration decision making by resource managers

Conflict in pedestrian networks

Encouraging pedestrian activity is increasingly recognised as beneficial for public health, the environment and the economy. As our cities become more crowded, there is a need for urban planners to take into account more explicitly pedestrian needs. The term that is now in use is that a city should be ‘walkable’. For route planning, whereas much attention has been given to shortest path, in distance or time, much less attention has been paid to flow levels and the difficulties they pose on the route. This paper considers problems posed by conflicting paths, for example cross-traffic. We use network centrality measures to make a first estimate of differing levels of conflict posed at the network nodes. We take special note of the role of collective motion in determining network usage. A small case study illustrates the method

Planning and Designing Walkable Cities: A Smart Approach

Walking may be considered one of the most sustainable and democratic ways of travelling within a city, thus providing benefits not only to pedestrians but also to the urban environment. Besides, walking is also one of the means of transport most likely subjected to factors outside an individual\u2019s control, like social or physical abilities to walk and the presence of comfortable and safe street infrastructures and services. Therefore, improving urban conditions provided to pedestrians has positive impacts on walkability. At the same time technological solutions and innovations have the power to encourage and support people to walk by overcoming immaterial barriers due to a lack of information or boring travel and they give to decision makers the possibility to gain data to understand how and where people travel. Merging these two dimensions into a unique approach can drastically improve accessibility, attractiveness, safety, comfort and security of urban spaces. In this context, this paper aims to draw a more multifaceted context for walkability, where new technologies assume a key role for introducing new approaches to pedestrian paths planning and design and thus for enhancing this mode of transport. Indeed, by combining more traditional spatial-based and perceptual analysis of the urban environment with technological applications and social media exploitation there will be room to better support the decision on and to enhance satisfaction of walking as well as to easier plan and design more walkable cities

Protocol for: Sheffield Obesity Trial (SHOT): A randomised controlled trial of exercise therapy and mental health outcomes in obese adolescents [ISRCNT83888112]

Background While obesity is known to have many physiological consequences, the psychopathology of this condition has not featured prominently in the literature. Cross-sectional studies have indicated that obese children have increased odds of experiencing poor quality of life and mental health. However, very limited trial evidence has examined the efficacy of exercise therapy for enhancing mental health outcomes in obese children, and the Sheffield Obesity Trial (SHOT) will provide evidence of the efficacy of supervised exercise therapy in obese young people aged 11–16 years versus usual care and an attention-control intervention. Method/design SHOT is a randomised controlled trial where obese young people are randomised to receive; (1) exercise therapy, (2) attention-control intervention (involving body-conditioning exercises and games that do not involve aerobic activity), or (3) usual care. The exercise therapy and attention-control sessions will take place three times per week for eight weeks and a six-week home programme will follow this. Ninety adolescents aged between 11–16 years referred from a children's hospital for evaluation of obesity or via community advertisements will need to complete the study. Participants will be recruited according to the following criteria: (1) clinically obese and aged 11–16 years (Body Mass Index Centile > 98th UK standard) (2) no medical condition that would restrict ability to be active three times per week for eight weeks and (3) not diagnosed with insulin dependent diabetes or receiving oral steroids. Assessments of outcomes will take place at baseline, as well as four (intervention midpoint) and eight weeks (end of intervention) from baseline. Participants will be reassessed on outcome measures five and seven months from baseline. The primary endpoint is physical self-perceptions. Secondary outcomes include physical activity, self-perceptions, depression, affect, aerobic fitness and BMI

Reliability and validity of three questionnaires measuring context-specific sedentary behaviour and associated correlates in adolescents, adults and older adults

BACKGROUND: Reliable and valid measures of total sedentary time, context-specific sedentary behaviour (SB) and its potential correlates are useful for the development of future interventions. The purpose was to examine test-retest reliability and criterion validity of three newly developed questionnaires on total sedentary time, context-specific SB and its potential correlates in adolescents, adults and older adults. METHODS: Reliability and validity was tested in six different samples of Flemish (Belgium) residents. For the reliability study, 20 adolescents, 22 adults and 20 older adults filled out the age-specific SB questionnaire twice. Test-retest reliability was analysed using Kappa coefficients, Intraclass Correlation Coefficients and/or percentage agreement, separately for the three age groups. For the validity study, data were retrieved from 62 adolescents, 33 adults and 33 older adults, with activPAL as criterion measure. Spearman correlations and Bland-Altman plots (or non-parametric approach) were used to analyse criterion validity, separately for the three age groups and for weekday, weekend day and average day. RESULTS: The test-retest reliability for self-reported total sedentary time indicated following values: ICC = 0.37-0.67 in adolescents; ICC = 0.73-0.77 in adults; ICC = 0.68-0.80 in older adults. Item-specific reliability results (e.g. context-specific SB and its potential correlates) showed good-to-excellent reliability in 67.94%, 68.90% and 66.38% of the items in adolescents, adults and older adults respectively. All items belonging to sedentary-related equipment and simultaneous SB showed good reliability. The sections of the questionnaire with lowest reliability were: context-specific SB (adolescents), potential correlates of computer use (adults) and potential correlates of motorized transport (older adults). Spearman correlations between self-reported total sedentary time and the activPAL were different for each age group: rho = 0.02-0.42 (adolescents), rho = 0.06-0.52 (adults), rho = 0.38-0.50 (older adults). Participants over-reported total sedentary time (except for weekend day in older adults) compared to the activPAL, for weekday, weekend day and average day respectively by +57.05%, +46.29%, +53.34% in adolescents; +40.40%, +19.15%, +32.89% in adults; +10.10%, -6.24%, +4.11% in older adults. CONCLUSIONS: The questionnaires showed acceptable test-retest reliability and criterion validity. However, over-reporting of total SB was noticeable in adolescents and adults. Nevertheless, these questionnaires will be useful in getting context-specific information on SB

The Escherichia coli transcriptome mostly consists of independently regulated modules

Underlying cellular responses is a transcriptional regulatory network (TRN) that modulates gene expression. A useful description of the TRN would decompose the transcriptome into targeted effects of individual transcriptional regulators. Here, we apply unsupervised machine learning to a diverse compendium of over 250 high-quality Escherichia coli RNA-seq datasets to identify 92 statistically independent signals that modulate the expression of specific gene sets. We show that 61 of these transcriptomic signals represent the effects of currently characterized transcriptional regulators. Condition-specific activation of signals is validated by exposure of E. coli to new environmental conditions. The resulting decomposition of the transcriptome provides: a mechanistic, systems-level, network-based explanation of responses to environmental and genetic perturbations; a guide to gene and regulator function discovery; and a basis for characterizing transcriptomic differences in multiple strains. Taken together, our results show that signal summation describes the composition of a model prokaryotic transcriptome

Diet, physical activity, and adiposity in children in poor and rich neighbourhoods: a cross-sectional comparison

BACKGROUND: Obesity in Canadian children increased three-fold in twenty years. Children living in low-income neighborhoods exercise less and are more overweight than those living in more affluent neighborhoods after accounting for family socio-economic status. Strategies to prevent obesity in children have focused on personal habits, ignoring neighborhood characteristics. It is essential to evaluate diet and physical activity patterns in relation to socio-economic conditions to understand the determinants of obesity. The objective of this pilot study was to compare diet, physical activity, and the built environment in two Hamilton area elementary schools serving socio-economically different communities. METHODS: We conducted a cross-sectional study (November 2005-March 2006) in two public elementary schools in Hamilton, Ontario, School A and School B, located in low and high socioeconomic areas respectively. We assessed dietary intake, physical activity, dietary restraint, and anthropometric measures in consenting children in grades 1 and higher. From their parents we assessed family characteristics and walkability of the built environment. RESULTS: 160 children (n = 48, School A and n = 112, School B), and 156 parents (n = 43, School A and n = 113, School B) participated in this study. The parents with children at School A were less educated and had lower incomes than those at School B. The School A neighborhood was perceived to be less walkable than the School B neighborhood. Children at School A consumed more baked foods, chips, sodas, gelatin desserts, and candies and less low fat dairy, and dark bread than those at School B. Children at School A watched more television and spent more time in front of the computer than children studying at School B, but reported spending less time sitting on weekdays and weekends. Children at both schools were overweight but there was no difference in their mean BMI z-scores (School A = 0.65 versus School B = 0.81, p-value = 0.38). CONCLUSION: The determinants of overweight in children may be more complex than imagined. In future intervention programs researchers may consider addressing environmental factors, and customizing lifestyle interventions so that they are closer to community needs

A Machine Learning Approach to Measure and Monitor Physical Activity in Children to Help Fight Overweight and Obesity

Physical Activity is important for maintaining healthy lifestyles. Recommendations for physical activity levels are issued by most governments as part of public health measures. As such, reliable measurement of physical activity for regulatory purposes is vital. This has lead research to explore standards for achieving this using wearable technology and artificial neural networks that produce classifications for specific physical activity events. Applied from a very early age, the ubiquitous capture of physical activity data using mobile and wearable technology may help us to understand how we can combat childhood obesity and the impact that this has in later life. A supervised machine learning approach is adopted in this paper that utilizes data obtained from accelerometer sensors worn by children in free-living environments. The paper presents a set of activities and features suitable for measuring physical activity and evaluates the use of a Multilayer Perceptron neural network to classify physical activities by activity type. A rigorous reproducible data science methodology is presented for subsequent use in physical activity research. Our results show that it was possible to obtain an overall accuracy of 96 % with 95 % for sensitivity, 99 % for specificity and a kappa value of 94 % when three and four feature combinations were used