ATLAS Pixel Detector System Test

On June 25th of 2007 the ATLAS collaboration lowered the pixel detector into place, however before this the detector had to be qualified through a series of tests. Prior to assembly, each individual piece of the detector and services chain passed a set of quality controls. This was followed by the construction and test of the whole pixel detector. This test of the full chain of services -including the voltage supplies, opto-boards, cooling, temperature monitoring, control software, and the pixel modules themselves- is referred to as the Pixel System Test. The System Test took place in an above-ground laboratory setting at CERN and consisted of two main parts. The first half of the test focused on one of the pixel detector’s endcaps. This endcap consists of 144 modules, making up roughly 10% of the total pixel detector. For the pixel endcap test, most of the 144 modules were operated simultaneously which required that the pixel endcap’s cooling system be functioning as well[1]. Additionally, four scintillators were added above and below the detector which trigged on cosmic muons. As a result, the pixel detector measured its first cosmic tracks during this test. After the cosmic test the pixel collaboration connected the entire pixel detector a few modules at a time. The cooling for the pixel detector could not be used in this setting, and to prevent overheating any componants only one chip was powered on at a time. This half of the system test is referred to as the connectivity test[3]

Observation of Instabilities of Coherent Transverse Ocillations in the Fermilab Booster

The Fermilab Booster - built more than 40 years ago - operates well above the design proton beam intensity of 4x10**12 ppp. Still, the Fermilab neutrino experiments call for even higher intensity of 5.5x10**12 ppp. A multitude of intensity related effects must be overcome in order to meet this goal including suppression of coherent dipole instabilities of transverse oscillations which manifest themselves as a sudden drop in the beam current. In this report we present the results of observation of these instabilities at different tune, coupling and chromaticity settings and discuss possible cures.Comment: 3 pp. 3rd International Particle Accelerator Conference (IPAC 2012) 20-25 May 2012, New Orleans, Louisian

Exercise and Recovery Responses of Lymphokines to Heavy Resistance Exercise

To examine the effect of dynamic resistance exercise on the response patterns of lymphokines, 10 strength-trained men (21.7 +- 0.6 y) performed 2 resistance exercise protocols, high force (HF) and high power (HP), of equal total work (HF 5 33.0 +- 2.5 kJ; HP 5 33.3 +- 2.7 kJ) in a randomized order separated by 1 week. Resting blood samples were obtained preexercise and 0 (R-0), 15 (R-15), and 240 (R-240) minutes postexercise. Plasma lactate significantly (p < 0.05) increased from baseline for both protocols; however, concentrations were higher in response to the HF protocol. Plasma interleukin- 2 (IL-2) concentrations were significantly decreased from baseline at R-15 following the HF protocol. Plasma interferon- gamma (IFN-g) concentrations decreased at R-0 following the HP protocol and returned to preexercise levels by R-15. Although the suppression of these 2 lymphokines was transient, the results indicate that the acute stress of high force and high resistance workouts induce differential IFN-g and IL-2 responses

The General Adaptation Syndrome: A Foundation For The Concept Of Periodization

Recent reviews have attempted to refute the efficacy of applying Selye’s general adaptation syndrome (GAS) as a conceptual framework for the training process. Furthermore, the criticisms involved are regularly used as the basis for arguments against the periodization of training. However, these perspectives fail to consider the entirety of Selye’s work, the evolution of his model, and the broad applications he proposed. While it is reasonable to critically evaluate any paradigm, critics of the GAS have yet to dismantle the link between stress and adaptation. Disturbance to the state of an organism is the driving force for biological adaptation, which is the central thesis of the GAS model and the primary basis for its application to the athlete’s training process. Despite its imprecisions, the GAS has proven to be an instructive framework for understanding the mechanistic process of providing a training stimulus to induce specific adaptations that result in functional enhancements. Pioneers of modern periodization have used the GAS as a framework for the management of stress and fatigue to direct adaptation during sports training. Updates to the periodization concept have retained its founding constructs while explicitly calling for scientifically based, evidence-driven practice suited to the individual. Thus, the purpose of this review is to provide greater clarity on how the GAS serves as an appropriate mechanistic model to conceptualize the periodization of training

Quercetin’s Influence on Exercise Performance and Muscle Mitochondrial Biogenesis

Purpose: To determine the influence of 2 wk of quercetin (Q; 1000 mg•d-1) compared with placebo (P) supplementation on exercise performance and skeletal muscle mitochondrial biogenesis in untrained, young adult males (N = 26, age = 20.2 ± 0.4 yr, V•O2max = 46.3 ± 1.2 mL•kg-1•min-1). Methods: Using a randomized, crossover design with a 2-wk washout period, subjects provided blood and muscle biopsy samples presupplementation and postsupplementation periods and were given 12-min time trials on 15% graded treadmills after 60 min of moderate exercise preloads at 60% V•O2max. Results: Plasma Q levels rose significantly in Q versus P during the 2-wk supplementation period (interaction P value <0.001). During the 12-min trial, the net change in distance achieved was significantly greater during Q (2.9%) compared with P (-1.2%; 29.5 ± 11.5 vs -11.9 ± 16.0 m, respectively, P = 0.038). Skeletal muscle messenger RNA expression tended to increase (range = 16-25%) during Q versus P for sirtuin 1 (interaction effect, P = 0.152), peroxisome proliferator-activated receptor [gamma] coactivator-1[alpha] (P = 0.192), cytochrome c oxidase (P = 0.081), and citrate synthase (P = 0.166). Muscle mitochondrial DNA (relative copy number per diploid nuclear genome) increased 140 ± 154 (4.1%) with Q compared with -225 ± 157 (6.0% decrease) with P (P = 0.098). Conclusions: In summary, 1000 mg•d-1 Q versus P for 2 wk by untrained males was associated with a small but significant improvement in 12-min treadmill time trial performance and modest but insignificant increases in the relative copy number of mitochondrial DNA and messenger RNA levels of four genes related to mitochondrial biogenesis

Influence of Resistance Exercise Volume on Serum Growth Hormone and Cortisol Concentrations in Women

Ten eumenorrheic women (age 24.1 ± 4.3) performed 2 randomly assigned heavy-resistance exercise protocols (HREP) on separate days during the early follicular phase of the menstrual cycle. Multiple-set (MS) HREP consisted of 3 sets of 10 RM of 8 resistance exercises with a I-min rest between exercises and sets. Single-set (55) HREP consisted of 1 set of 10 RM of the same 8 exercises in the same order, with I-min rest between consecutive exercises. 55 total work was about onethird that of the MS. Immunoreactive serum growth hormone (GH), cortisol, and blood lactate were measured pre- and postexercise (0, 15, and 30 min). The MS produced significant (p < 0.05) increases in serum GH and cortisol above resting levels at all postexercise times. The 55 significantly increased serum GH at 15 min postexercise, and cortisol at 0 and 15 min postexercise. Both protocols yielded Significant increases in blood lactate above rest at all postexercise times. The MS produced the most significant hormonal and metabolic responses, indicating that exercise volume may be an important factor in hormonal and metabolic mechanisms related to resistance exercise in women

Does Short-Term Near-Maximal Intensity Machine Resistance Training Induce Overtraining?

To examine the efficacy of a 3-week, high-intensity, resistance exercise protocol for inducing overtraining, 9 subjects trained their lower body on a squat-simulating resistance exercise machine. Five subjects performed a training (Trn) protocol 5 days a week to elicit an overtraining response. Four subjects performed a control (Con) protocol 2 days a week. Test batteries of sprints, jumps, and strength tests were performed four times during the study at I-week intervals (Tl, T2, T3, T4). One-RM performances increased for the Trn group by T2 and remained augmented through T4. Overtraining did not occur, but other performances were attenuated for the Tm group. Increased sprint times for 9.1 m and 36.6 m were evident by T2 for the Tm group and remained slower through T4. Leg extension torque decreased for the Trn group by T4. Future attempts to induce intensity-dependent overtraining for study should use greater training intensities or different training modalities and should monitor phYSiological factors that may contribute to this phenomenon

Comparison of Methods to Quantify Volume During Resistance Exercise

The purpose of this investigation was to compare 4 different methods of calculating volume when comparing resistance exercise protocols of varying intensities. Ten Appalachian State University students experienced in resistance exercise completed 3 different resistance exercise protocols on different days using a randomized, crossover design, with 1 week of rest between each protocol. The protocols included 1) hypertrophy: 4 sets of 10 repetitions in the squat at 75% of a 1-repetition maximum (1RM) (90-second rest periods); 2) strength: 11 sets of 3 repetitions at 90% 1RM (5-minute rest periods); and 3) power: 8 sets of 6 repetitions of jump squats at 0% 1RM (3-minute rest periods). The volume of resistance exercise completed during each protocol was determined with 4 different methods: 1) volume load (VL) (repetitions [no.] 3 external load [kg]); 2) maximum dynamic strength volume load (MDSVL) (repetitions [no.] 3 [body mass 2 shank mass (kg) + external load (kg)]); 3) time under tension (TUT) (eccentric time +milliseconds] + concentric time +milliseconds]); and 4) total work (TW) (force [N] X displacement [m]). The volumes differed significantly (p < 0.05) between hypertrophy and strength in comparison with the power protocol when VL and MDSVL were used to determine the volume of resistance exercise completed. Furthermore, significant differences in TUT existed between all 3 resistance exercise protocols. The TW calculated was not significantly different between the 3 protocols. These data imply that each method examined results in substantially different values when comparing various resistance exercise protocols involving different levels of intensity

Testing of the Maximal Dynamic Output Hypothesis in Trained and Untrained Subjects

The maximal dynamic output (MDO) hypothesis is a newly proposed concept, which suggests that the muscular system of the lower limbs is designed to produce maximal power output when performing countermovement vertical jumping (CMJ) at body mass as opposed to other loading conditions. However, it is unclear if the MDO concept can be applied to individuals with different levels of maximal strength. The purpose of this investigation was to determine if subjects, who have distinct differences in maximal strength, maximize CMJ power at body mass. Fourteen male strength-power trained subjects (squat 1 repetition maximum (1RM)-to-body mass ratio = 1.96 +- 0.24) and 6 untrained male subjects (squat 1RM-to-body mass ratio = 0.94 +- 0.18) completed CMJs with loads that were less than, equal to, and greater than body mass. Loads less than body mass were accomplished with a custom-designed unloading apparatus, and loads greater than body mass were accomplished with a barbell and weights. In both groups, mean values for CMJ peak and mean power were greatest during the body mass jump. Power outputs at body mass were significantly different (p <= 0.05) than power outputs at various conditions of loading and unloading. These data support the MDO hypothesis and its application to individuals with significantly different 1RM-to-body mass ratios. Additionally, these data further support the idea that body mass CMJs are a theoretically sound way to train for power because of the maximal power outputs that are produced during this condition

Impact of Training Patterns on Incidence of Illness and Injury During a Women's Collegiate Basketball Season

This study was conducted to monitor the training patterns throughout a basketball season in order to determine if a relationship exists between the physical stress of practice and the occurrence of injuries and illnesses in NCAA Division III athletes. Subjects consisted of college women (n = 12) ranging in age from 18 to 22 years. A certified athletic trainer distributed a questionnaire following each practice, including 2 weeks of preseason, documenting the presence of injury, illness, or both, relative to the intensity and duration of practice. Training load, training monotony, and training strain were computed using the session rate of perceived exertion scale method. An increase in injuries occurred during times of increased training loads, particularly during the first 2 weeks of formal practice, and immediately subsequent to the holidays. The temporal relationship between training load and injury suggests a causative link (p < 0.01; r = 0.675). The present data suggest that the periodization pattern of basketball training may be linked to the likelihood of illness/ injury