Oxygen consumption and muscle activation patterns during constant load exercise

The collective purpose of these two studies was to determine a link between the V02 slow component and the muscle activation patterns that occur during cycling. Six, male subjects performed an incremental cycle ergometer exercise test to determine asub-TvENT (i.e. 80% of TvENT) and supra-TvENT (TvENT + 0.75*(V02 max - TvENT) work load. These two constant work loads were subsequently performed on either three or four occasions for 8 mins each, with V02 captured on a breath-by-breath basis for every test, and EMO of eight major leg muscles collected on one occasion. EMG was collected for the first 10 s of every 30 s period, except for the very first 10 s period. The V02 data was interpolated, time aligned, averaged and smoothed for both intensities. Three models were then fitted to the V02 data to determine the kinetics responses. One of these models was mono-exponential, while the other two were biexponential. A second time delay parameter was the only difference between the two bi-exponential models. An F-test was used to determine significance between the biexponential models using the residual sum of squares term for each model. EMO was integrated to obtain one value for each 10 s period, per muscle. The EMG data was analysed by a two-way repeated measures ANOV A. A correlation was also used to determine significance between V02 and IEMG. The V02 data during the sub-TvENT intensity was best described by a mono-exponential response. In contrast, during supra-TvENT exercise the two bi-exponential models best described the V02 data. The resultant F-test revealed no significant difference between the two models and therefore demonstrated that the slow component was not delayed relative to the onset of the primary component. Furthermore, only two parameters were deemed to be significantly different based upon the two models. This is in contrast to other findings. The EMG data, for most muscles, appeared to follow the same pattern as V02 during both intensities of exercise. On most occasions, the correlation coefficient demonstrated significance. Although some muscles demonstrated the same relative increase in IEMO based upon increases in intensity and duration, it cannot be assumed that these muscles increase their contribution to V02 in a similar fashion. Larger muscles with a higher percentage of type II muscle fibres would have a larger increase in V02 over the same increase in intensity.

Real-time performance modelling of a sustained attention to response task

Vigilance declines when exposed to highly predictable and uneventful tasks. Monotonous tasks provide little cognitive and motor stimulation and contribute to human errors. This paper aims to model and detect vigilance decline in real time through participant’s reaction times during a monotonous task. A lab-based experiment adapting the Sustained Attention to Response Task (SART) is conducted to quantify the effect of monotony on overall performance. Then relevant parameters are used to build a model detecting hypovigilance throughout the experiment. The accuracy of different mathematical models are compared to detect in real-time – minute by minute - the lapses in vigilance during the task. We show that monotonous tasks can lead to an average decline in performance of 45%. Furthermore, vigilance modelling enables to detect vigilance decline through reaction times with an accuracy of 72% and a 29% false alarm rate. Bayesian models are identified as a better model to detect lapses in vigilance as compared to Neural Networks and Generalised Linear Mixed Models. This modelling could be used as a framework to detect vigilance decline of any human performing monotonous tasks.

Best practices in prediction for decision-making : lessons from the atmospheric and earth sciences

Predictions that result from scientific research hold great appeal for decision-makers who are grappling with complex and controversial environmental issues, by promising to enhance their ability to determine a need for and outcomes of alternative decisions. A problem exists in that decision-makers and scientists in the public and private sectors solicit, produce, and use such predictions with little understanding of their accuracy or utility, and often without systematic evaluation or mechanisms of accountability. In order to contribute to a more effective role for ecological science in support of decision-making, this paper discusses three ``best practices'' for quantitative ecosystem modeling and prediction gleaned from research on modeling, prediction, and decision-making in the atmospheric and earth sciences. The lessons are distilled from a series of case studies and placed into the specific context of examples from ecological science.

Shoot growth dynamics and photosynthetic response to increased nitrogen availability in the alpine willow salix-glauca

Plants subjected to increases in the supply of resource(s) limiting growth may allocate more of those resources to existing leaves, increasing photosynthetic capacity, and/or to production of more leaves, increasing whole-plant photosynthesis. The responses of three populations of the alpine willow, Salix glauca, growing along an alpine topographic sequence representing a gradient in soil moisture and organic matter, and thus potential N supply, to N amendments, were measured over two growing seasons, to elucidate patterns of leaf versus shoot photosynthetic responses. Leaf-(foliar N, photosynthesis rates, photosynthetic N-use efficiency) and shoot-(leaf area per shoot, number of leaves per shoot, stem weight, N resorption efficiency) level measurements were made to examine the spatial and temporal variation in these potential responses to increased N availability. The predominant response of the willows to N fertilization was at the shoot-level, by production of greater leaf area per shoot. Greater leaf area occurred due to production of larger leaves in both years of the experiment and to production of more leaves during the second year of fertilization treatment. Significant leaf-level photosynthetic response occurred only during the first year of treatment, and only in the dry meadow population. Variation in photosynthesis rates was related more to variation in stomatal conductance than to foliar N concentration. Stomatal conductance in turn was significantly related to N fertilization. Differences among the populations in photosynthesis, foliar N, leaf production, and responses to N fertilization indicate N availability may be lowest in the dry meadow population, and highest in the ridge population. This result is contrary to the hypothesis that a gradient of plant available N corresponds with a snowpack/topographic gradient.

Response of cells on surface-induced nanopatterns: Fibroblasts and mesenchymal progenitor cells

Ultrathin films of a poly(styrene)-block-poly(2-vinylpyrindine) diblock copolymer (PS-b-P2VP) and poly(styrene)-block-poly(4-vinylpyrindine) diblock copolymer (PS-b-P4VP) were used to form surface-induced nanopattern (SINPAT) on mica. Surface interaction controlled microphase separation led to the formation of chemically heterogeneous surface nanopatterns on dry ultrathin films. Two distinct nanopatterned surfaces, namely, wormlike and dotlike patterns, were used to investigate the influence of topography in the nanometer range on cell adhesion, proliferation, and migration. Atomic force microscopy was used to confirm that SINPAT was stable under cell culture conditions. Fibroblasts and mesenchymal progenitor cells were cultured on the nanopatterned surfaces. Phase contrast and confocal laser microscopy showed that fibroblasts and mesenchymal progenitor cells preferred the densely spaced wormlike patterns. Atomic force microscopy showed that the cells remodelled the extracellular matrix differently as they migrate over the two distinctly different nanopatterns