ZERO SOUND-VELOCITY IN PI, RHO-MESON GASES

Sharp transitions are perhaps absent in QCD, so that one looks for physical quantities which may reflect the phase change. One such quantity is the sound velocity which was shown in lattice theory to become zero at the transition point for pure glue. We show that even in a simple bag model the sound velocity goes to zero at temperature T = T(v) not-equal 0 and that the numerical value of this T(v) depends on the nature of the meson. The average thermal energy of mesons goes linearly with T near T(v), with much smaller slope for the pion. The T(v) - s can be connected with the Boltzmann temperatures obtained from transverse momentum spectrum of these mesons in heavy-ion collision at mid-rapidity. It would be interesting to check the presence of different T(v) - s in present day finite T lattice theory.

Relationships and significance of lactate minimum, critical velocity, heart rate deflection and 3 000 m track-tests for running

The running velocities associated to lactate minimum (V-lm), heart rate deflection (V-HRd), critical velocity (CV), 3000 M (V-3000) and 10000 m performance (V-10km) were compared. Additionally the ability of V-lm and VHRd on identifying sustainable velocities was investigated.Methods. Twenty runners (28.5 +/- 5.9 y) performed 1) 3000 m running test for V3000; 2) an all-out 500 in sprint followed by 6x800 m incremental bouts with blood lactate ([lac]) measurements for V-lm; 3) a continuous velocity-incremented test with heart rate measurements at each 200 m for V-HRd; 4) participants attempted to 30 min of endurance test both at V-lm(ETVlm) and V-HRd(ETVHRd). Additionally, the distance-time and velocity-1/time relationships produced CV by 2 (500 m and 3000 m) or 3 predictive trials (500 m, 3000 m and distance reached before exhaustion during ETVHRd), and a 10 km race was recorded for V-10km.Results. The CV identified by different methods did not differ to each other. The results (m(.)min(-1)) revealed that V-.(lm) (281 +/- 14.8)< CV (292.1 +/- 17.5)=V-10km (291.7 +/- 19.3)< V-HRd (300.8 +/- 18.7)=V-3000 (304 +/- 17.5) with high correlation among parameters (P < 0.001). During ETVlm participants completed 30 min of running while on the ETVHRd they lasted only 12.5 +/- 8.2 min with increasing [lac].Conclusion. We evidenced that CV and Vim track-protocols are valid for running evaluation and performance prediction and the parameters studied have different significance. The V-lm reflects the moderate-high intensity domain (below CV), can be sustained without [lac] accumulation and may be used for long-term exercise while the V-HRd overestimates a running intensity that can be sustained for long-time. Additionally, V-3000 and V-HRd reflect the severe intensity domain (above CV).

Interval training at 95% and 100% of the velocity at VO2 max: effects on aerobic physiological indexes and running performance

The objective of this study was to analyze the effect of two different high-intensity interval training (HIT) programs on selected aerobic physiological indices and 1500 and 5000 m running performance in well-trained runners. The following tests were completed (n = 17): (i) incremental treadmill test to determine maximal oxygen uptake (VO2max), running velocity associated with VO2 max (VVO2max), and the velocity corresponding to 3.5 mmol/L of blood lactate concentration (vOBLA); (ii) submaximal constant-intensity test to determine running economy (RE); and (iii) 1500 and 5000 m time trials on a 400 m track. Runners were then randomized into 95% vVO(2max) or 100% vVO(2max) groups, and undertook a 4 week training program consisting of 2 HIT sessions (performed at 95% or 100% vVO(2max), respectively) and 4 submaximal run sessions per week. Runners were retested on all parameters at the completion of the training program. The VO2 max values were not different after training for both groups. There was a significant increase in post-training vVO(2 max), RE, and 1500 in running performance in the 100% vVO(2 max) group. The vOBLA and 5000 m running performance were significantly higher after the training period for both groups. We conclude that vOBLA and 5000 m running performance can be significantly improved in well-trained runners using a 4 week training program consisting of 2 HIT sessions (performed at 95% or 100% vVO(2max)) and 4 submaximal run sessions per week. However, the improvement in vVO(2 max), RE, and 1500 in running performance seems to be dependent on the HIT program at 100% vVO(2 max).

Particle Competition and Cooperation in Networks for Semi-Supervised Learning with Concept Drift

Concept drift is a problem of increasing importance in machine learning and data mining. Data sets under analysis are no longer only static databases, but also data streams in which concepts and data distributions may not be stable over time. However, most learning algorithms produced so far are based on the assumption that data comes from a fixed distribution, so they are not suitable to handle concept drifts. Moreover, some concept drifts applications requires fast response, which means an algorithm must always be (re) trained with the latest available data. But the process of labeling data is usually expensive and/or time consuming when compared to unlabeled data acquisition, thus only a small fraction of the incoming data may be effectively labeled. Semi-supervised learning methods may help in this scenario, as they use both labeled and unlabeled data in the training process. However, most of them are also based on the assumption that the data is static. Therefore, semi-supervised learning with concept drifts is still an open challenge in machine learning. Recently, a particle competition and cooperation approach was used to realize graph-based semi-supervised learning from static data. In this paper, we extend that approach to handle data streams and concept drift. The result is a passive algorithm using a single classifier, which naturally adapts to concept changes, without any explicit drift detection mechanism. Its built-in mechanisms provide a natural way of learning from new data, gradually forgetting older knowledge as older labeled data items became less influent on the classification of newer data items. Some computer simulation are presented, showing the effectiveness of the proposed method.

Nonmodal energetics of resistive drift waves

The modal and nonmodal linear properties of the Hasegawa-Wakatani system are examined. This linear model for plasma drift waves is nonnormal in the sense of not having a complete set of orthogonal eigenvectors. A consequence of nonnormality is that finite-time nonmodal growth rates can be larger than modal growth rates. In this system, the nonmodal time-dependent behavior depends strongly on the adiabatic parameter and the time scale of interest. For small values of the adiabatic parameter and short time scales, the nonmodal growth rates, wave number, and phase shifts (between the density and potential fluctuations) are time dependent and differ from those obtained by normal mode analysis. On a given time scale, when the adiabatic parameter is less than a critical value, the drift waves are dominated by nonmodal effects while for values of the adiabatic parameter greater than the critical value, the behavior is that given by normal mode analysis. The critical adiabatic parameter decreases with time and modal behavior eventually dominates. The nonmodal linear properties of the Hasegawa-Wakatani system may help to explain features of the full system previously attributed to nonlinearity.

Nonmodal energetics of electromagnetic drift waves

The linear properties of an electromagnetic drift-wave model are examined. The linear system is non-normal in that its eigenvectors are not orthogonal with respect to the energy inner product. The non-normality of the linear evolution operator can lead to enhanced finite-time growth rates compared to modal growth rates. Previous work with an electrostatic drift-wave model found that nonmodal behavior is important in the hydrodynamic limit. Here, similar behavior is seen in the hydrodynamic regime even with the addition of magnetic fluctuations. However, unlike the results for the electrostatic drift-wave model, nonmodal behavior is also important in the adiabatic regime with moderate to strong magnetic fluctuations. © 2000 American Institute of Physics.

A low-voltage programmable-gain CMOS amplifier with very-low temperature-drift

A new topology for a LVLP variable-gain CMOS amplifier is presented. Input- and load-stage are built around triode-transconductors so that voltage-gain is fully defined by a linear relationship involving only device-geometries and biases. Excellent gain-accuracy, temperature-insensitivity; and wide range of programmability, are thus achieved. Moreover, adaptative biasing improves the common-mode voltage stability upon gain-adjusting. As an example, a 0-40dB programmablegain audio-amplifier is designed. Its performance is supported by a range of simulations. For VDD=1.8V and 20dB-nominal gain, one has Av=19.97dB, f3db=770KHz and quiescent dissipation of 378μW. Over temperatures from -25°C to 125°C, the 0. ldB-bandwidth is 52KHz. Dynamic-range is optimized to 57.2dB and 42.6dB for gains of 20dB and 40dB, respectively. THD figures correspond to -60.6dB@Vout= 1Vpp and -79.7dB@Vout= 0.5 Vpp. A nearly constant bandwidth for different gains is also attained.

The relationship between onset of blood lactate accumulation, critical velocity, and maximal lactate steady state in soccer players

The objective of this study was to analyze the validity of the velocity corresponding to the onset of blood lactate accumulation (OBLA) and critical velocity (CV) to determine the maximal lactate steady state (MLSS) in soccer players. Twelve male soccer players (21.5 ± 1.0 years) performed an incremental treadmill test for the determination of OBLA. The velocity corresponding to OBLA (3.5 mM of blood lactate) was determined through linear interpolation. The subjects returned to the laboratory on 7 occasions for the determination of MLSS and CV. The MLSS was determined from 5 treadmill runs of up to 30-minute duration and defined as the highest velocity at which blood lactate did not increase by more than 1 mM between minutes 10 and 30 of the constant velocity runs. The CV was determined by 2 maximal running efforts of 1,500 and 3,000 m performed on a 400-m running track. The CV was calculated as the slope of the linear regression of distance run versus time. Analysis of variance revealed no significant differences between OBLA (13.6 ± 1.4 km·h-1) and MLSS (13.1 ± 1.2 km·h-1) and between OBLA and CV (14.4 ± 1.1 km·h-1). The CV was significantly higher than the MLSS. There was a significant correlation between MLSS and OBLA (r = 0.80), MLSS and CV (r = 0.90), and OBLA and CV (r = 0.80). We can conclude that the OBLA can be utilized in soccer players to estimate the MLSS. In this group of athletes, however, CV does not represent a sustainable steady-state exercise intensity. © 2005 National Strength & Conditioning Association.

Effects of gender on stroke rates, critical speed and velocity of a 30-min swim in young swimmers

Our objective was to analyze the effect of gender on the relationship between stroke rates corresponding to critical speed (SRCS) and maximal speed of 30 min (SRS30) in young swimmers. Twenty two males (GM1) (Age = 15.4 ± 2.1 yr., Body mass = 63.7 ± 12.9 kg, Stature = 1.73 ± 0.09 m) and fourteen female (GF) swimmers (Age = 15.1 ± 1.6 yr., Body mass = 58.3 ± 8.8 kg, Stature = 1.65 ± 0.06 m) were studied. A subset of males (GM2) was matched to the GF by their velocity for a 30 min swim (S30). The critical speed (CS) was determined through the slope of the linear regression line between the distances (200 and 400 m) and participant's respective times. CS was significantly higher than S30 in males (GM1 - 1.25 and 1.16 and GM2 - 1.21 and 1.12 m·s-1) and females (GF - 1.15 and 1.11 m·s-1). There was no significant difference between SRCS and SRS30 in males (GM1 - 34.16 and 32.32 and GM2 - 34.67 and 32.46 cycle·s-1, respectively) and females (GF - 34.18 and 33.67 cycle·s-1-1, respectively). There was a significant correlation between CS and S30 (GM1 - r = 0.89, GF - r = 0.94 and GM2 - r = 0.90) and between SRCS and SRS30 (GM1 - r = 0.89, GF - r = 0.80 and GM2 - r = 0.88). Thus, the relationship between SRCS and SRS30 is not influenced by gender, in swimmers with similar and different aerobic capacity levels. ©Journal of Sports Science and Medicine (2007).