This study’s purpose was to examine heart rate variability (HRV) and direct current potential (DC) measures’ sensitivity and correlations between changes in the acute recovery and stress scale (ARSS) and the previous day’s training load. Training load, HRV, DC and ARSS data were collected from fourteen professional mixed martial arts athletes (32.6 ± 5.3 years, 174.8 ± 8.8 cm, 79.2 ± 17.5 kg) the following morning after hard, easy and rest days. Sensitivity was expressed as a signal-to-noise ratio (SNR, inter-day typical error (TE) or coefficient of variation (%CV) divided by intra-day TE or %CV). Correlations between HRV, DC and ARSS with training load were also examined. The SNRs for the various HRV and DC measures were acceptable to good (1.02–2.85). There was a 23.1% CV average increase between measures taken between different locations versus the same location. Training load changes were not correlated with HRV/DC but were correlated with ARSS stress variables. Practitioners should be aware of HRV/DC variability; however the daily training signal was greater than the test-retest error in this investigation. Upon awakening, HRV/DC measures appear superior for standardization and planning. HRV and DC measures were less sensitive to the previous day’s training load than ARSS measures.

No abstract

RESUMENSe estudiaron los cambios en la inhibición presináptica de las motoneuronas espinales α durante actividades motoras de diferentes tipos. En un estado de reposo relativo de los músculos, la inhibición presináptica de las motoneuronas espinales α del músculo soleus era más fuerte en «samboístas» (atletas especializados en el arte marcial sambo) y en velocistas que en corredores de fondo. En los samboístas que realizaron cargas estáticas repetidas, la inhibición presináptica de las motoneuronas espinales α fue aumentando de un intento al siguiente. Tanto el entrenamiento en técnica como en fuerza aumentaron la inhibición presináptica de las motoneuronas espinales α, de forma más acentuada después del entrenamiento en fuerza.

Fomin R, Sergeev V, Nesterik K, Kosminin V. Effect of intense muscular activity on motor potentials under magnetic stimulation of brain and spinal cord. J. Hum. Sport Exerc. Vol. 5, No. 3, pp. 348-357, 2010. In this work, the parameters of motor evoked potentials of upper and lower extremity muscles were evaluated, under magnetic stimulation of cerebral cortex motor areas, spinal segments, and nerve tibialis in athletes adapted to work of various duration and intensity (sprinters, stayers) and having various qualifications. It was established that the maximum amplitude of the motor evoked potentials of muscle gastrocnemius med. and muscle soleus under transcranial magnetic stimulation of the brain is higher in the stayer group than in sprinters. High qualification ski racers, in comparison with lower qualification ski racers, have lower excitation thresholds and a higher maximum amplitude of the motor evoked potentials of muscles carpi radialis, biceps brahii, gastrocnemius med., and soleus. No statistically significant differences in the central motor conduction time and the latent period of motor evoked potentials have been revealed between the compared groups of persons being tested.

A major oilfield services provider was requested by a Russian national oil company to conduct a study of a tight, naturally fractured reservoir in Algeria. The goal was to integrate multiple data types (borehole images, wireline acoustic data, 360-degree core photographs) to generate a representative set of 3D static models describing the natural fracture network (with optimistic, basic and pessimistic cases) and then define fracture permeability. The reservoir is a tight Ordovician sandstone with intensive faulting, a complex facies pattern, and limited well data—all presenting significant challenges. Fracture interpretation was integrated from different sources, including borehole images, cross multipole acoustic data and 360-degree core photographs. The integration of fracture data from so many sources based on different physical principles enabled fracture modelling with much higher confidence, providing an input for further field development. The workflow for fracture density determination is divided into several stages: from borehole imaging (including definition of open, mixed and closed fracture types) and acoustic data fracture interpretation to 3D fracture density trend creation and calibration. Image interpretation results show good correlation to acoustic log interpretation results using Stoneley reflectivity and azimuthal anisotropy analysis. Combining acoustic, core and image logs data allowed organization of the wellbores into fracture classes. Fracture classes are zones of probability about the presence of natural fractures. These classes vary from very high probability (where all data types show presence of fractures) to zero probability (where all data types show no fractures or anisotropy). The 3D model of fracture density reflects a basic concept: the fracture density decreases away from fault cores, and within the fault cores the fracture density is at a maximum. This observation was supported by many field analogues (including some in Algeria). There were many intervals of intensive natural fracturing that were identified from images and core photographs. These zones might have contributed significantly to fracture permeability. This idea is supported by well test data analysis: the effective permeability from well tests significantly exceeds the matrix (core) permeability but is within the range of fracture permeability as defined by the continuous fracture network (CFN) modelling. Various data sets were integrated and calibrated to enable precise identification of fracture density distribution, fracture classes, and dip angle and aperture of natural fractures. These data sets provided input for fracture permeability calculations. Fracture density, fracture aperture and fracture dip angle 3D grids were prepared. Special equations, developed for tight, fractured Algerian sandstones, were applied to calculate fracture properties, e.g., fracture permeability. Through the close interaction of a multi-disciplinary team it was possible to successfully build a consistent 3D CFN model and to perform fracture uncertainty analysis to determine a variety of high-, mid- and low-fractured permeability cases. This model also supported further 1D and 3D geomechanical modelling studies. This CFN model provided a rapid workflow and robust model for further field development planning and new well placement.