title: The effect of eccentric cycle training on physiological and performance parameters in cycling.

authors: Dillon, Piers, Callum

abstract: Prior research has demonstrated the benefits of 3 to 8 weeks of eccentric cycle  training in athletes, the elderly, and in suffers of various pathophysiological conditions. Eccentric cycling requires participants to absorb force generated by an electric motor that drives a traditional cycle crank in a reverse fashion. Relative to traditional concentric cycle training, eccentric cycling is lower in metabolic cost and facilitates greater force production through multi-joint leg actions.  
Chapter 2 reports on an investigation that utilises an eccentric cycling ergometer to evaluate and observe the influence of eccentric cycle training on a range of key performance parameters, and physiological measures on a well-trained cycling population. Specifically, in this novel study we assessed the physiological performance measures of leg spring stiﬀness, 4 s mean maximal sprint power, 4-km time-trial performance, and economy prior to, during, and following periodised eccentric cycle training. The investigation recruited eight healthy well-trained male participants (mean ± SD; age: 33 ± 12 yr; mass: 80 ± 11 kg; VO₂peak: 64 ± 8 ml.kg⁻¹.min⁻¹) to take part in a 6 week, 12 session eccentric cycling study. Utilising a commercially available eccentric ergometer (Cyclus2, Leipzig, Germany), the participants replaced two hours of their weekly cycle training, with eccentric cycling. Initial training loads were prescribed based on 25% of participant 4 s mean maximal sprint power (MM4SP). Stepwise increases of training load occurred every 3ʳᵈ training session. Assessments of submaximal hopping to evaluate leg spring stiﬀness, 4 s mean maximal sprint power and 4-km time-trial performance were conducted, prior-to, during the 3ʳᵈ week (Mid), and 1 and 4 weeks following the eccentric cycling intervention. Over a 6 week period, this stepwise approach led to an increase in workload from 25% to 50% of participant MM4SP. Overall participants achieved 97 ± 4% of their individual prescribed training load during the 6 week eccentric cycling training intervention.  
Relative to baseline measures, muscle stiffness effects were very likely positive (35.8 ± 30.4%) at week 3 (Mid), and at 1 week post (57.7 ± 22.3 and 46.6 ± 26.0%) week 4 post intervention. Effects for 4 s mean maximal sprint power were likely beneficial at 60 rpm at week 11 relative to both baseline, and week 7. Similarly, likely beneficial effects were reported at 120 (week 7 – pre), and 135 rpm (week 11 – pre). 4-km time-trial performance, at Mid (mean ± SD %: 0.2 ± 2.8%), and 1 week (0.7 ± 2.3%) post-training produced unclear alterations, while likely beneficial improvements were seen at week 4 (2.3 ± 3.6%) post-training. The findings of the current study suggest that 12 sessions of eccentric training over a 6 week period improved 4-km time-trial performance, and muscle stiffness within a well-trained population. Outcomes for the remaining endurance and sprint performance related measures however predominantly resulted as unaltered or unclear over the participant population

text: The effect of eccentric cycle training on physiological and performance parameters in cycling. Prior research has demonstrated the benefits of 3 to 8 weeks of eccentric cycle  training in athletes, the elderly, and in suffers of various pathophysiological conditions. Eccentric cycling requires participants to absorb force generated by an electric motor that drives a traditional cycle crank in a reverse fashion. Relative to traditional concentric cycle training, eccentric cycling is lower in metabolic cost and facilitates greater force production through multi-joint leg actions.  
Chapter 2 reports on an investigation that utilises an eccentric cycling ergometer to evaluate and observe the influence of eccentric cycle training on a range of key performance parameters, and physiological measures on a well-trained cycling population. Specifically, in this novel study we assessed the physiological performance measures of leg spring stiﬀness, 4 s mean maximal sprint power, 4-km time-trial performance, and economy prior to, during, and following periodised eccentric cycle training. The investigation recruited eight healthy well-trained male participants (mean ± SD; age: 33 ± 12 yr; mass: 80 ± 11 kg; VO₂peak: 64 ± 8 ml.kg⁻¹.min⁻¹) to take part in a 6 week, 12 session eccentric cycling study. Utilising a commercially available eccentric ergometer (Cyclus2, Leipzig, Germany), the participants replaced two hours of their weekly cycle training, with eccentric cycling. Initial training loads were prescribed based on 25% of participant 4 s mean maximal sprint power (MM4SP). Stepwise increases of training load occurred every 3ʳᵈ training session. Assessments of submaximal hopping to evaluate leg spring stiﬀness, 4 s mean maximal sprint power and 4-km time-trial performance were conducted, prior-to, during the 3ʳᵈ week (Mid), and 1 and 4 weeks following the eccentric cycling intervention. Over a 6 week period, this stepwise approach led to an increase in workload from 25% to 50% of participant MM4SP. Overall participants achieved 97 ± 4% of their individual prescribed training load during the 6 week eccentric cycling training intervention.  
Relative to baseline measures, muscle stiffness effects were very likely positive (35.8 ± 30.4%) at week 3 (Mid), and at 1 week post (57.7 ± 22.3 and 46.6 ± 26.0%) week 4 post intervention. Effects for 4 s mean maximal sprint power were likely beneficial at 60 rpm at week 11 relative to both baseline, and week 7. Similarly, likely beneficial effects were reported at 120 (week 7 – pre), and 135 rpm (week 11 – pre). 4-km time-trial performance, at Mid (mean ± SD %: 0.2 ± 2.8%), and 1 week (0.7 ± 2.3%) post-training produced unclear alterations, while likely beneficial improvements were seen at week 4 (2.3 ± 3.6%) post-training. The findings of the current study suggest that 12 sessions of eccentric training over a 6 week period improved 4-km time-trial performance, and muscle stiffness within a well-trained population. Outcomes for the remaining endurance and sprint performance related measures however predominantly resulted as unaltered or unclear over the participant population

year: 2018

title: Classic and spatial shift-share analysis of state-level employment change in Brazil

authors: Matlaba, Valente José

subjects: Regional employment

abstract: This paper combines classic and spatial shift-share decompositions of 1981 to 2006 employment change across the 27 states of Brazil. The classic shift-share method shows higher employment growth rates for underdeveloped regions that are due to an advantageous industry-mix and also due to additional job creation, commonly referred to as the competitive effect. Alternative decompositions proposed in the literature do not change this broad conclusion. Further examination employing exploratory spatial data analysis (ESDA) shows spatial correlation of both the industry-mix and the competitive effects. Considering that until the 1960s economic activities were more concentrated in southern regions of Brazil than they are nowadays, these results support beta convergence theories but also find evidence of agglomeration effects. Additionally, a very simple spatial decomposition is proposed that accounts for the spatially-weighted growth of surrounding states. Favourable growth in northern and centre-western states is basically associated with those states’ strengths in potential spatial spillover effect and in spatial competitive effect.

text: Classic and spatial shift-share analysis of state-level employment change in Brazil This paper combines classic and spatial shift-share decompositions of 1981 to 2006 employment change across the 27 states of Brazil. The classic shift-share method shows higher employment growth rates for underdeveloped regions that are due to an advantageous industry-mix and also due to additional job creation, commonly referred to as the competitive effect. Alternative decompositions proposed in the literature do not change this broad conclusion. Further examination employing exploratory spatial data analysis (ESDA) shows spatial correlation of both the industry-mix and the competitive effects. Considering that until the 1960s economic activities were more concentrated in southern regions of Brazil than they are nowadays, these results support beta convergence theories but also find evidence of agglomeration effects. Additionally, a very simple spatial decomposition is proposed that accounts for the spatially-weighted growth of surrounding states. Favourable growth in northern and centre-western states is basically associated with those states’ strengths in potential spatial spillover effect and in spatial competitive effect.

year: 2012-07

title: Does artificial intelligence modelling have anything to offer traditional management of freshwater food resources?

authors: Death, Russell G.

abstract: Management of freshwater systems and the ecosystem services they provide has become a multi-stakeholder activity. This requires information on resources and how to manage them to be disseminated to a wide range of users. While artificial intelligence modelling can provide a powerful tool in managing and understanding resources and their drivers, they can be confusing to many users. In this study, we explored the potential use of two alternative modelling approaches (Boosted Regression Trees (BRT) and Bayesian Belief Networks (BBN)) for managing three species of freshwater mahinga kai species-kākahi or kaeo (freshwater mussel), koura (freshwater crayfish) and tuna (freshwater eel). While the BBN model I sbetter for stakeholder communication, the BRT produced more accurate models for all species. However, variables identified as being important for predicting abundance and biomass of these species were often environmental parameters that cannot be managed to improve yield. The artificial intelligence modelling does provide some accurate linkages between the target species and their environmental drivers. Nevertheless, translating these relationships into management plans remains challenging. The models are clearly not a panacea for better resource management, but provide one more tool that might assist multi-stakeholder understanding of how best to manage freshwater resources.

text: Does artificial intelligence modelling have anything to offer traditional management of freshwater food resources? Management of freshwater systems and the ecosystem services they provide has become a multi-stakeholder activity. This requires information on resources and how to manage them to be disseminated to a wide range of users. While artificial intelligence modelling can provide a powerful tool in managing and understanding resources and their drivers, they can be confusing to many users. In this study, we explored the potential use of two alternative modelling approaches (Boosted Regression Trees (BRT) and Bayesian Belief Networks (BBN)) for managing three species of freshwater mahinga kai species-kākahi or kaeo (freshwater mussel), koura (freshwater crayfish) and tuna (freshwater eel). While the BBN model I sbetter for stakeholder communication, the BRT produced more accurate models for all species. However, variables identified as being important for predicting abundance and biomass of these species were often environmental parameters that cannot be managed to improve yield. The artificial intelligence modelling does provide some accurate linkages between the target species and their environmental drivers. Nevertheless, translating these relationships into management plans remains challenging. The models are clearly not a panacea for better resource management, but provide one more tool that might assist multi-stakeholder understanding of how best to manage freshwater resources.

year: 2017