Wing shape as a potential discriminator of morphologically similar pest taxa within the Bactrocera dorsalis species complex (Diptera: Tephritidae)

Four morphologically cryptic species of the Bactrocera dorsalis fruit fly complex (B. dorsalis s.s., B. papayae, B. carambolae and B. philippinensis) are serious agricultural pests. As they are difficult to diagnose using traditional taxonomic techniques, we examined the potential for geometric morphometric analysis of wing size and shape to discriminate between them. Fifteen wing landmarks generated size and shape data for 245 specimens for subsequent comparisons among three geographically distinct samples of each species. Intraspecific wing size was significantly different within samples of B. carambolae and B. dorsalis s.s. but not within samples of B. papayae or B. philippinensis. Although B. papayae had the smallest wings (average centroid size=6.002 mm±0.061 SE) and B. dorsalis s.s. the largest (6.349 mm±0.066 SE), interspecific wing size comparisons were generally non-informative and incapable of discriminating species. Contrary to the wing size data, canonical variate analysis based on wing shape data discriminated all species with a relatively high degree of accuracy; individuals were correctly reassigned to their respective species on average 93.27% of the time. A single sample group of B. carambolae from locality 'TN Malaysia' was the only sample to be considerably different from its conspecific groups with regards to both wing size and wing shape. This sample was subsequently deemed to have been originally misidentified and likely represents an undescribed species. We demonstrate that geometric morphometric techniques analysing wing shape represent a promising approach for discriminating between morphologically cryptic taxa of the B. dorsalis species complex.

Does the effect of weight lifting on lymphedema following breast cancer differ by diagnostic method: results from a randomized controlled trial

The lymphedema diagnostic method used in descriptive or intervention studies may influence results found. The purposes of this work were to compare baseline lymphedema prevalence in the physical activity and lymphedema (PAL) trial cohort and to subsequently compare the effect of the weight-lifting intervention on lymphedema, according to four standard diagnostic methods. The PAL trial was a randomized controlled intervention study, involving 295 women who had previously been treated for breast cancer, and evaluated the effect of 12 months of weight lifting on lymphedema status. Four diagnostic methods were used to evaluate lymphedema outcomes: (i) interlimb volume difference through water displacement, (ii) interlimb size difference through sum of arm circumferences, (iii) interlimb impedance ratio using bioimpedance spectroscopy, and (iv) a validated self-report survey. Of the 295 women who participated in the PAL trial, between 22 and 52% were considered to have lymphedema at baseline according to the four diagnostic criteria used. No between-group differences were noted in the proportion of women who had a change in interlimb volume, interlimb size, interlimb ratio, or survey score of ≥5, ≥5, ≥10%, and 1 unit, respectively (cumulative incidence ratio at study end for each measure ranged between 0.6 and 0.8, with confidence intervals spanning 1.0). The variation in proportions of women within the PAL trial considered to have lymphoedema at baseline highlights the potential impact of the diagnostic criteria on population surveillance regarding prevalence of this common morbidity of treatment. Importantly though, progressive weight lifting was shown to be safe for women following breast cancer, even for those at risk or with lymphedema, irrespective of the diagnostic criteria used.

Does metabolic compensation explain the majority of less-than-expected weight loss in obese adults during a short-term severe diet and exercise intervention?

Objective: We investigated to what extent changes in metabolic rate and composition of weight loss explained the less-than-expected weight loss in obese men and women during a diet-plus-exercise intervention. Design: 16 obese men and women (41 ± 9 years; BMI 39 ± 6 kg/m2) were investigated in energy balance before, after and twice during a 12-week VLED (565–650 kcal/day) plus exercise (aerobic plus resistance training) intervention. The relative energy deficit (EDef) from baseline requirements was severe (74-87%). Body composition was measured by deuterium dilution and DXA and resting metabolic rate (RMR) by indirect calorimetry. Fat mass (FM) and fat-free mass (FFM) were converted into energy equivalents using constants: 9.45 kcal/gFM and 1.13 kcal/gFFM. Predicted weight loss was calculated from the energy deficit using the '7700 kcal/kg rule'. Results: Changes in weight (-18.6 ± 5.0 kg), FM (-15.5 ± 4.3 kg), and FFM (-3.1 ± 1.9 kg) did not differ between genders. Measured weight loss was on average 67% of the predicted value, but ranged from 39 to 94%. Relative EDef was correlated with the decrease in RMR (R=0.70, P<0.01) and the decrease in RMR correlated with the difference between actual and expected weight loss (R=0.51, P<0.01). Changes in metabolic rate explained on average 67% of the less-than-expected weight loss, and variability in the proportion of weight lost as FM accounted for a further 5%. On average, after adjustment for changes in metabolic rate and body composition of weight lost, actual weight loss reached 90% of predicted values. Conclusion: Although weight loss was 33% lower than predicted at baseline from standard energy equivalents, the majority of this differential was explained by physiological variables. While lower-than-expected weight loss is often attributed to incomplete adherence to prescribed interventions, the influence of baseline calculation errors and metabolic down-regulation should not be discounted.

Multi-objective design optimization of morphing UAV aerofoil/wing using hybridised MOGA

The paper investigates two advanced Computational Intelligence Systems (CIS) for a morphing Unmanned Aerial Vehicle (UAV) aerofoil/wing shape design optimisation. The first CIS uses Genetic Algorithm (GA) and the second CIS uses Hybridized GA (HGA) with the concept of Nash-Equilibrium to speed up the optimisation process. During the optimisation, Nash-Game will act as a pre-conditioner. Both CISs; GA and HGA, are based on Pareto optimality and they are coupled to Euler based Computational Fluid Dynamic (CFD) analyser and one type of Computer Aided Design (CAD) system during the optimisation.

Large scale monocular vision-only mapping from a fixed-wing sUAS

This paper presents the application of a monocular visual SLAMon a fixed-wing small Unmanned Aerial System (sUAS) capable of simultaneous estimation of aircraft pose and scene structure. We demonstrate the robustness of unconstrained vision alone in producing reliable pose estimates of a sUAS, at altitude. It is ultimately capable of online state estimation feedback for aircraft control and next-best-view estimation for complete map coverage without the use of additional sensors.We explore some of the challenges of visual SLAM from a sUAS including dealing with planar structure, distant scenes and noisy observations. The developed techniques are applied on vision data gathered from a fast-moving fixed-wing radio control aircraft flown over a 1×1km rural area at an altitude of 20-100m.We present both raw Structure from Motion results and a SLAM solution that includes FAB-MAP based loop-closures and graph-optimised pose. Timing information is also presented to demonstrate near online capabilities. We compare the accuracy of the 6-DOF pose estimates to an off-the-shelfGPS aided INS over a 1.7kmtrajectory.We also present output 3D reconstructions of the observed scene structure and texture that demonstrates future applications in autonomous monitoring and surveying.

Piecing together an integrative taxonomic puzzle: microsatellite, wing shape and aedeagus length analyses of Bactrocera dorsalis s.l. (Diptera: Tephritidae) find no evidence of multiple lineages in a proposed contact zone along the Thai/Malay Peninsula

Bactrocera dorsalis (Hendel) and B. papayae Drew & Hancock represent a closely related sibling species pair for which the biological species limits are unclear; i.e., it is uncertain if they are truely two biological species, or one biological species which has been incorrectly taxonomically split. The geographic ranges of the two taxa are thought to abut or overlap on or around the Isthmus of Kra, a recognised biogeographic barrier located on the narrowest portion of the Thai Peninsula. We collected fresh material of B. dorsalis sensu lato (i.e., B. dorsalis sensu stricto + B. papayae) in a north-south transect down the Thai Peninsula, from areas regarded as being exclusively B. dorsalis s.s., across the Kra Isthmus, and into regions regarded as exclusively B. papayae. We carried out microsatellite analyses and took measurements of male genitalia and wing shape. Both the latter morphological tests have been used previously to separate these two taxa. No significant population structuring was found in the microsatellite analysis and results were consistent with an interpretation of one, predominantly panmictic population. Both morphological datasets showed consistent, clinal variation along the transect, with no evidence for disjunction. No evidence in any tests supported historical vicariance driven by the Isthmus of Kra, and none of the three datasets supported the current taxonomy of two species. Rather, within and across the area of range overlap or abutment between the two species, only continuous morphological and genetic variation was recorded. Recognition that morphological traits previously used to separate these taxa are continuous, and that there is no genetic evidence for population segregation in the region of suspected species overlap, is consistent with a growing body of literature that reports no evidence of biological differentiation between these taxa.

Weight bias on psychological and physical health

It is a round table discussion article. "Weight bias refers to negative weight-related attitudes and beliefs, expressed in a range of forms towards individuals who are overweight or obese. Consequences of weight bias could be very significant to the individuals which may predispose them to additional weight gain. This brief literature review discusses the concept of weight bias and its impact on psychological and physical health on overweight and obese individuals..."

The interaction between exercise, appetite and food intake : implications for weight control

Exercise could indirectly affect body weight by exerting changes on various components of appetite control, including nutrient and taste preferences, meal size and frequency, and the drive to eat. This review summarizes the evidence on how exercise affects appetite and eating behavior and in particular answers the question, “Does exercise induce an increase in food intake to compensate for the increase in energy expenditure?” Evidence will be presented to demonstrate that there is no automatic increase in food intake in response to acute exercise and that the response to repeated exercise is variable. The review will also identify areas of further study required to explain the variability. One limitation with studies that assess the efficacy of exercise as a method of weight control is that only mean data are presented—the individual variability tends to be overlooked. Recent evidence highlights the importance of characterizing the individual variability by demonstrating exercise-induced changes in appetite. Individuals who experience lower than theoretically predicted reductions in body weight can be characterized by hedonic (eg, pleasure) and homeostatic (eg, hunger) features.

Exercise, appetite and weight management: understanding the compensatory responses in eating behaviour and how they contribute to variability in exercise-induced weight loss

Does exercise promote weight loss? One of the key problems with studies assessing the efficacy of exercise as a method of weight management and obesityis that mean data are presented and the individual variability in response is overlooked. Recent data have highlighted the need to demonstrate and characterise the individual variability in response to exercise. Do people who exercise compensate for the increase in energy expenditure via compensatory increases in hunger and food intake? The authors address the physiological, psychological and behavioural factors potentially involved in the relationship between exercise and appetite, and identify the research questions that remain unanswered. A negative consequence of the phenomena of individual variability and compensatory responses has been the focus on those who lose little weight in response to exercise; this has been used unreasonably as evidence to suggest that exercise is a futile method of controlling weight and managing obesity. Most of the evidence suggests that exercise is useful for improving body composition and health. For example, when exercise-induced mean weight loss is <1.0 kg, significant improvements in aerobic capacity (+6.3 ml/kg/min), systolic (−6.00 mm Hg) and diastolic (−3.9 mm Hg) blood pressure, waist circumference (−3.7 cm) and positive mood still occur. However, people will vary in their responses to exercise; understanding and characterising this variability will help tailor weight loss strategies to suit individuals.

Diet, physical activity and substrate oxidation : implications for appetite control, weight loss and body composition

In many countries, governments and health agencies are strongly promoting physical activity as a means to prevent the accumulation of fatness that leads to weight gain and obesity. However, there is often a resistance to respond to health promotion initiatives. For example, in the UK, the Chief Medical Officer has recently reported that 71% of women and 61% of men fail to carry out even the minimal amount of physical activity recommended in the government’s guidelines. Similarly, the Food safety Agency has promoted reductions in the intake of fat, sugar and salt but with very little impact on the pattern of consumption. Why is it that recommendations to improve health are so difficult to implement, and produce the desired outcome?