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Coordinative couplings are commonly classified as interpersonal and intrapersonal. Interpersonal coordination is normally thought of as between organisms but a subset can also be considered where the co-actors movements are coupled to an environmental rhythm. This can be termed extrapersonal coordination. This study explores how coordination is achieved in a situation that demands that at least one actor makes use of extrapersonal sources. In this case multi-seat rowing, where one actor cannot see the other one behind them. A qualitative approach using experiential knowledge from expert rowers (N=9) and coaches (N=4) was used to examine how interpersonal coordination was achieved and maintained in 2 person rowing boats. It was reported that where possible, both rowers coordinated their movements by coupling with an invariant provided by the boat. This invariant is underpinned by perception of water flow past the boat; which is in turn used to determine changes in acceleration - 'rowing with the boat.' Bow seat also identified the rower in front and stroke seat identified the looming of the stern as viable alternative sources for coupling.

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., (© 2011 Adis Data Information BV. All rights reserved.)

Premise of the Study: Leaves at the tops of most trees are smaller, thicker, and in many other ways different from leaves on the lowermost branches. This height-related variation in leaf structure has been explained as acclimation to differing light environments and, alternatively, as a consequence of hydrostatic, gravitational constraints on turgor pressure that reduce leaf expansion. •, Methods: To separate hydrostatic effects from those of light availability, we used anatomical analysis of height-paired samples from the inner and outer tree crowns of tall redwoods (Sequoia sempervirens). •, Key Results: Height above the ground correlates much more strongly with leaf anatomy than does light availability. Leaf length, width, and mesophyll porosity all decrease linearly with height and help explain increases in leaf-mass-to-area ratio and decreases in both photosynthetic capacity and internal gas-phase conductance with increasing height. Two functional traits-leaf thickness and transfusion tissue-also increase with height and may improve water-stress tolerance. Transfusion tissue area increases enough that whole-leaf vascular volume does not change significantly with height in most trees. Transfusion tracheids become deformed with height, suggesting they may collapse under water stress and act as a hydraulic buffer that improves leaf water status and reduces the likelihood of xylem dysfunction. •, Conclusions: That such variation in leaf structure may be caused more by gravity than by light calls into question use of the terms "sun" and "shade" to describe leaves at the tops and bottoms of tall tree crowns.

The primary purpose of this study was to determine whether a range of static core stability (CS) measures could distinguish shoulder press performance in unstable vs. stable conditions. Thirty resistance-trained men gave informed consent to participate in this study. One-repetition maximum strength (from < 6 repetitions) was predicted in the seated shoulder dumbbell press performed in unstable (Swiss ball[SB]) and stable (back-support bench) environments. Three CS muscle endurance tests were performed, with 4 CS ratios also calculated. The degree of strength decrement, referred to as the instability strength level (ISL), was calculated by dividing the predicted 1RM Unstable score by the 1RM Stable score. All subjects were categorized as high (ISL > 0.90), moderate (0.85 < or = ISL < or = 0.90), or low (ISL < 0.85). Between-group differences for the high- and low-ISL groups were assessed using analysis of variance and effect sizes. Pearson product moment correlations were then performed to examine the relationships between the CS measures and the ISL for the entire group. No significant between-group differences (p = 0.132-0.999) or large effect sizes were observed for any of the CS measures. Trunk flexion endurance was the only CS measure significantly correlated to the ISL (r = 0.477). In line with muscular strength research, these results suggest that CS exhibits relatively high levels of task specificity and that CS performance in static single-joint exercises may not be highly related to that in more dynamic multijoint activities. Core stability training (with or without a SB) may therefore only lead to significant improvements in functional dynamic performance if the postures, mode and velocity of contraction performed in training, are similar to the competitive tasks.

Past research has revealed that central vision is more important than peripheral vision in controlling the amplitude of target-directed aiming movements. However, the extent to which central vision contributes to movement planning versus online control is unclear. Since participants usually fixate the target very early in the limb trajectory, the limb enters the central visual field during the late stages of movement. Hence, there may be insufficient time for central vision to be processed online to correct errors during movement execution. Instead, information from central vision may be processed offline and utilised as a form of knowledge of results, enhancing the programming of subsequent trials. In the present research, variability in limb trajectories was analysed to determine the extent to which peripheral and central vision is used to detect and correct errors during movement execution. Participants performed manual aiming movements of 450 ms under four different visual conditions: full vision, peripheral vision, central vision, no vision. The results revealed that participants utilised visual information from both the central and peripheral visual fields to adjust limb trajectories during movement execution. However, visual information from the central visual field was used more effectively to correct errors online compared to visual information from the peripheral visual field.

To determine whether lung transfer factor for carbon monoxide (T(L(CO))) alters during menstrual phase and if steroid hormone levels relate to these changes, T(L(CO)) and T(L(CO)) adjusted for both alveolar volume (T(L)/V(A)) and haemoglobin concentration, were measured at five predefined and hormonally confirmed menstrual phases in 13 women. No difference between phases was observed in T(L(CO)) or adjusted values. Moreover, there was no association between the maximal change in oestradiol, progesterone, or oestradiol:progesterone ratio and the change in T(L(CO)) measured at the same time. When the first five chronological measurements, regardless of the menstrual phase at which they were measured, were analysed, T(L(CO)) changed significantly (p<0.05) with a maximal change between the first and fourth test (-2.69+/-2.53, 95% confidence interval). Although these results indicate that the first in a series of T(L(CO)) measurements may be higher, we found neither menstrual cycle phase nor ovarian hormone-related changes in T(L(CO)), and conclude that its adjustment for menstrual phase may not be necessary.