Block training periodization in alpine skiing: effects of 11-day HIT on VO2max and performance

Attempting to achieve the high diversity of training goals in modern competitive alpine skiing simultaneously can be difficult and may lead to compromised overall adaptation. Therefore, we investigated the effect of block training periodization on maximal oxygen consumption (VO2max) and parameters of exercise performance in elite junior alpine skiers. Six female and 15 male athletes were assigned to high-intensity interval (IT, N = 13) or control training groups (CT, N = 8). IT performed 15 high-intensity aerobic interval (HIT) sessions in 11 days. Sessions were 4 x 4 min at 90-95% of maximal heart rate separated by 3-min recovery periods. CT continued their conventionally mixed training, containing endurance and strength sessions. Before and 7 days after training, subjects performed a ramp incremental test followed by a high-intensity time-to-exhaustion (tlim) test both on a cycle ergometer, a 90-s high-box jump test as well as countermovement (CMJ) and squat jumps (SJ) on a force plate. IT significantly improved relative VO2max by 6.0% (P < 0.01; male +7.5%, female +2.1%), relative peak power output by 5.5% (P < 0.01) and power output at ventilatory threshold 2 by 9.6% (P < 0.01). No changes occurred for these measures in CT. tlim remained unchanged in both groups. High-box jump performance was significantly improved in males of IT only (4.9%, P < 0.05). Jump peak power (CMJ -4.8%, SJ -4.1%; P < 0.01), but not height decreased in IT only. For competitive alpine skiers, block periodization of HIT offers a promising way to efficiently improve VO2max and performance. Compromised explosive jump performance might be associated with persisting muscle fatigue.

Comparative assessment of conventional and self-ligating appliances on the effect of mandibular intermolar distance in adolescent nonextraction patients: a single-center randomized controlled trial

Our aim in this study was to compare intermolar widths after alignment of crowded mandibular dental arches in nonextraction adolescent patients between conventional and self-ligating brackets.

Distance measures for image segmentation evaluation

The task considered in this paper is performance evaluation of region segmentation algorithms in the ground-truth-based paradigm. Given a machine segmentation and a ground-truth segmentation, performance measures are needed. We propose to consider the image segmentation problem as one of data clustering and, as a consequence, to use measures for comparing clusterings developed in statistics and machine learning. By doing so, we obtain a variety of performance measures which have not been used before in image processing. In particular, some of these measures have the highly desired property of being a metric. Experimental results are reported on both synthetic and real data to validate the measures and compare them with others.