Similar metabolic adaptations during exercise after low volume sprint interval and traditional endurance training in humans

Low-volume ‘sprint’ interval training (SIT) stimulates rapid improvements in muscle oxidative capacity that are comparable to levels reached following traditional endurance training (ET) but no study has examined metabolic adaptations during exercise after these different training strategies. We hypothesized that SIT and ET would induce similar adaptations in markers of skeletal muscle carbohydrate (CHO) and lipid metabolism and metabolic control during exercise despite large differences in training volume and time commitment. Active but untrained subjects (23 ± 1 years) performed a constant-load cycling challenge (1 h at 65% of peak oxygen uptake before and after 6 weeks of either SIT or ET (n = 5 men and 5 women per group). SIT consisted of four to six repeats of a 30 s ‘all out’ Wingate Test (mean power output ∼500 W) with 4.5 min recovery between repeats, 3 days per week. ET consisted of 40–60 min of continuous cycling at a workload that elicited ∼65% (mean power output ∼150 W) per day, 5 days per week. Weekly time commitment (∼1.5 versus ∼4.5 h) and total training volume (∼225 versus ∼2250 kJ week−1) were substantially lower in SIT versus ET. Despite these differences, both protocols induced similar increases (P < 0.05) in mitochondrial markers for skeletal muscle CHO (pyruvate dehydrogenase E1α protein content) and lipid oxidation (3-hydroxyacyl CoA dehydrogenase maximal activity) and protein content of peroxisome proliferator-activated receptor-γ coactivator-1α. Glycogen and phosphocreatine utilization during exercise were reduced after training, and calculated rates of whole-body CHO and lipid oxidation were decreased and increased, respectively, with no differences between groups (all main effects, P < 0.05). Given the markedly lower training volume in the SIT group, these data suggest that high-intensity interval training is a time-efficient strategy to increase skeletal muscle oxidative capacity and induce specific metabolic adaptations during exercise that are comparable to traditional ET.

Neurophysiological responses after short-term strength training of the biceps brachii muscle

The neural adaptations that mediate the increase in strength in the early phase of a strength training program are not well understood; however, changes in neural drive and corticospinal excitability have been hypothesized. To determine the neural adaptations to strength training, we used transcranial magnetic stimulation (TMS) to compare the effect of strength training of the right elbow flexor muscles on the functional properties of the corticospinal pathway. Motorevoked potentials (MEPs) were recorded from the right biceps brachii (BB) muscle from 23 individuals (training group; n = 13 and control group; n = 10) before and after 4 weeks of progressive overload strength training at 80% of 1-repetition maximum (1 RM). The TMS was delivered at 10% of the root mean square electromyographic signal (rmsEMG) obtained from a maximal voluntary contraction (MVC) at intensities of 5% of stimulator output below active motor threshold (AMT) until saturation of the MEP (MEP maxl. Strength training resulted in a 28% (p = 0.0001) increase in 1 RM strength, and this was accompanied by a 53% increase (p = 0.05) in the amplitude of the MEP at AMT; 33% (p = 0.05) increase in MEP at 20% above AMT, and a 38% increase at MEPmax (p = 0.04). There were no significant differences in the estimated slope (p = 0.4 7) or peak slope of the stimulus-response curve for the left primary motor cortex (M1) after strength training (p = 0.61). These results demonstrate that heavy-load isotonic strength training alters neural transmission via the corticospinal pathway projecting to the motoneurons controlling BB and in part underpin the strength changes observed in this study.

Strength training of one limb increases corticomotor excitability projecting to the contralateral homologous limb

The contralateral transfer of strength following unilateral strength training (ULS) is thought to be due to changes within the nervous system. Using transcranial magnetic stimulation (TMS) we compared corticospinal responses following ULS of the right biceps brachii (BB) projecting to the untrained left BB. Motor evoked potentials (MEPs) were recorded from both BB of 23 individuals pre and post 4 weeks heavy load (80% of 1RM) ULS of right BB. TMS was delivered at intensities below active motor threshold (AMT) to saturation of the MEP (MEP_max). ULS resulted in a 28% increase in 1RM right BB strength, resulting in a 19.2% increase in contralateral strength of the left BB (p = .0001). There was a significant increase in MEP amplitude of 30.3% (p = .03), 33% (p = .05), and 26.5% (p = .01) at AMT, 20% above AMT and MEP_max respectively. No significant differences in silent period were seen at AMT, 20% above AMT or MEP_max. This study has demonstrated increased corticospinal excitability projecting to the untrained arm following heavy load ULS.

Gymnasium-based unsupervised exercise maintains benefits in oxygen uptake kinetics obtained following supervised training in type 2 diabetes

Supervised exercise (SE) in patients with type 2 diabetes improves oxygen uptake kinetics at the onset of exercise. Maintenance of these improvements, however, has not been examined when supervision is removed. We explored if potential improvements in oxygen uptake kinetics following a 12-week SE that combined aerobic and resistance training were maintained after a subsequent 12-week unsupervised exercise (UE). The involvement of cardiac output (CO) in these improvements was also tested. Nineteen volunteers with type 2 diabetes were recruited. Oxygen uptake kinetics and CO (inert gas rebreathing) responses to constant-load cycling at 50% ventilatory threshold (V_T), 80% V_T, and mid-point between V_T and peak workload (50% Δ) were examined at baseline (on 2 occasions) and following each 12-week training period. Participants decided to exercise at a local gymnasium during the UE. Thirteen subjects completed all the interventions. The time constant of phase 2 of oxygen uptake was significantly faster (p < 0.05) post-SE and post-UE compared with baseline at 50% V_T (17.3 ± 10.7 s and 17.5 ± 5.9 s vs. 29.9 ± 10.7 s), 80% V_T (18.9 ± 4.7 and 20.9 ± 8.4 vs. 34.3 ± 12.7s), and 50% Δ (20.4 ± 8.2 s and 20.2 ± 6.0 s vs. 27.6 ± 3.7 s). SE also induced faster heart rate kinetics at all 3 intensities and a larger increase in CO at 30 s in relation to 240 s at 80% V_T; and these responses were maintained post-UE. Unsupervised exercise maintained benefits in oxygen uptake kinetics obtained during a supervised exercise in subjects with diabetes, and these benefits were associated with a faster dynamic response of heart rate after training.

Influence of grain size and training temperature on strain of polycrystalline Ni50Mn29Ga21 samples

The alloy Ni-Mn-Ga aroused great interest for application as a magnetic shape memory (MSM) material. This effect is caused by reorientation of twin variants by an external magnetic field. So far, most of the experiments were concentrated on single crystals. But, the MSM effect can also be realised in polycrystals which can be prepared much more efficiently. Here, polycrystalline samples were prepared by directional solidification with a <100> fibre texture of the high temperature cubic austenitic phase parallel to the heat flow. Afterwards, a heat treatment was applied for chemical homogenisation and stress relaxation in the austenitic state. Then the samples were heated up to the austenitic state and cooled down under load. The microstructure was analysed by Electron Back Scatter Diffraction (EBSD) before and after that treatment. Mechanical training at room temperature and 40°C was tracked by recording stress-strain curves. By increasing the number of training cycles the strain also increases. The influence of different training temperatures was investigated on samples with different grain sizes.

Short term load forecasting using a hybrid neural network

Short Term Load Forecasting (STLF) is very important from the power systems grid operation point of view. STLF involves forecasting load demand in a short term time frame. The short term time frame may consist of half hourly prediction up to weekly prediction. Accurate forecasting would benefit the utility in terms of reliability and stability of the grid ensuring adequate supply is present to meet with the load demand. Apart from that it would also affect the financial performance of the utility company. An accurate forecast would result in better savings while maintaining the security of the grid. This paper outlines the STLF using a novel hybrid online learning neural network, known as the Gaussian Regression (GR). This new hybrid neural network is a combination of two existing online learning neural networks which are the Gaussian Adaptive Resonance Theory (GA) and the Generalized Regression Neural Network (GRNN). Both GA and GRNN implemented online learning, but each of them suffers from limitation. Originally GA is used for unsupervised clustering by compressing the training samples into several categories. A supervised version of GA is available, namely Gaussian ARTMAP (GAM). However, the GAM is still not capable on solving regression problem. On the other hand, GRNN is designed for solving real value estimation (regression) problem, but the learning process would involve of memorizing all training samples, hence high computational cost. The hybrid GR is considered an enhanced version of GRNN with compression ability while still maintains online learning properties. Simulation results show that GR has comparable prediction accuracy and has less prototype as compared to the original GRNN as well as the Support Vector Regression.

Quantification of physical load in elite junior Australian football players

Results from this thesis provide insights into the physical loads experienced by the elite junior Australian footballer. The information presented can assist in the facilitation of best practice advice for player management and training prescription through the use of training diaries and GPS TMA and HR device technologies.

Improving load forecasting accuracy through combination of best forecasts

Neural network (NN) models have been widely used in the literature for short-term load forecasting. Their popularity is mainly due to their excellent learning and approximation capability. However, their forecasting performance significantly depends on several factors including initializing parameters, training algorithm, and NN structure. To minimize negative effects of these factors, this paper proposes a practically simple, yet effective and an efficient method to combine forecasts generated by NN models. The proposed method includes three main phases: (i) training NNs with different structures, (ii) selecting best NN models based on their forecasting performance for a validation set, and (iii) combination of forecasts for selected best NNs. Forecast combination is performed through calculating the mean of forecasts generated by best NN models. The performance of the proposed method is examined using real world data set. Comparative studies demonstrate that the accuracy of combined forecasts is significantly superior to those obtained from individual NN models.

Anodal tDCS applied during strength training enhances motor cortical plasticity

Purpose:
The objective of this study was to assess the effect of anodal transcranial direct current stimulation (a-tDCS) on voluntary dynamic strength and cortical plasticity when applied during a 3-wk strength training program for the wrist extensors.

Methods:
Thirty right-handed participants were randomly allocated to the tDCS, sham, or control group. The tDCS and sham group underwent 3 wk of heavy-load strength training of the right wrist extensors, with 20 min of a-tDCS (2 mA) or sham tDCS applied during training (double blinded). Outcome measures included voluntary dynamic wrist extension strength, muscle thickness, corticospinal excitability, short-interval intracortical inhibition (SICI), and silent period duration.

Results:
Maximal voluntary strength increased in both the tDCS and sham groups (14.89% and 11.17%, respectively, both P < 0.001). There was no difference in strength gain between the two groups (P = 0.229) and no change in muscle thickness (P = 0.15). The tDCS group demonstrated an increase in motor-evoked potential amplitude at 15%, 20%, and 25% above active motor threshold, which was accompanied by a decrease in SICI during 50% maximal voluntary isometric contraction and 20% maximal voluntary isometric contraction (all P < 0.05). Silent period decreased for both the tDCS and sham groups (P < 0.001).

Conclusion:
The application of a-tDCS in combination with strength training of the wrist extensors in a healthy population did not provide additional benefit for voluntary dynamic strength gains when compared with standard strength training. However, strength training with a-tDCS appears to differentially modulate cortical plasticity via increases in corticospinal excitability and decreases in SICI, which did not occur following strength training alone

Short-term intensified cycle training alters acute and chronic responses of PGC1α and cytochrome C oxidase IV to exercise in human skeletal muscle

Reduced activation of exercise responsive signalling pathways have been reported in response to acute exercise after training; however little is known about the adaptive responses of the mitochondria. Accordingly, we investigated changes in mitochondrial gene expression and protein abundance in response to the same acute exercise before and after 10-d of intensive cycle training.

Nine untrained, healthy participants (mean±SD; VO2peak 44.1±17.6 ml/kg/min) performed a 60 min bout of cycling exercise at 164±18 W (72% of pre-training VO2peak). Muscle biopsies were obtained from the vastus lateralis muscle at rest, immediately and 3 h after exercise. The participants then underwent 10-d of cycle training which included four high-intensity interval training sessions (6×5 min; 90–100% VO2peak) and six prolonged moderate-intensity sessions (45–90 min; 75% VO2peak). Participants repeated the pre-training exercise trial at the same absolute work load (64% of pre-training VO2peak). Muscle PGC1-α mRNA expression was attenuated as it increased by 11- and 4- fold (P<0.001) after exercise pre- and post-training, respectively. PGC1-α protein expression increased 1.5 fold (P<0.05) in response to exercise pre-training with no further increases after the post-training exercise bout. RIP140 protein abundance was responsive to acute exercise only (P<0.01). COXIV mRNA (1.6 fold; P<0.01) and COXIV protein expression (1.5 fold; P<0.05) were increased by training but COXIV protein expression was decreased (20%; P<0.01) by acute exercise pre- and post-training.

These findings demonstrate that short-term intensified training promotes increased mitochondrial gene expression and protein abundance. Furthermore, acute indicators of exercise-induced mitochondrial adaptation appear to be blunted in response to exercise at the same absolute intensity following short-term training.

Prediction intervals for electricity load forecasting using neural networks

Most of the research in time series is concerned with point forecasting. In this paper we focus on interval forecasting and its application for electricity load prediction. We extend the LUBE method, a neural network-based method for computing prediction intervals. The extended method, called LUBEX, includes an advanced feature selector and an ensemble of neural networks. Its performance is evaluated using Australian electricity load data for one year. The results showed that LUBEX is able to generate high quality prediction intervals, using a very small number of previous lag variables and having acceptable training time requirements. The use of ensemble is shown to be critical for the accuracy of the results.

Common variants of the resistance mechanism in the Smith Machine: analysis of mechanical loading characteristics and application to strength-oriented and hypertrophy-oriented training

The Smith machine is a pervasive weight-training apparatus, used extensively by a wide population of weight trainers, from novices to high-level athletes. The advantages of using a Smith machine over free-weight resistance are disputed, with conflicting findings reported in the literature. In this study, we are interested in practical differences between 3 types of loading mechanisms found in modern Smith machines. In addition to the basic design comprising a constrained weighted barbell, alterations with a counterweight and a viscous resistance component are examined. The approach taken is that of employing a recently proposed representation of force characteristics that may be exhibited by a trainee and a predictive model of thus effected adaptation. A computer simulation is used to predict the effects of the 3 linear Smith machine designs in the framework of different exercise protocols. Our results demonstrate that each resistance component, vertically constrained load, counterweight, and viscous, can be matched with a particular training context, in which it should be preferred. Thus, a number of practical guidelines for weight-training practitioners are recommended. In summary, (a) at low intensities (55–75% of 1 repetition maximum [1RM]) used in strength-endurance training, a viscous resistance containing the Smith machine was found to offer advantages over both a constrained load only and counterweighted designs; (b) at medium intensities (75–85% of 1RM) typically employed in hypertrophy-specific training, the counterweighted Smith machine design was found to offer the best choice in terms of high-force development and total external work performed; finally, (c) at high training intensity (90–100% of 1RM), the optimal prescription was found to be more dependent on the specific athlete’s weaknesses, highlighting the need for continual monitoring of the athlete’s force production capabilities. To ensure that appropriate adjustments are made to the athlete’s training regimen, the practitioner should consider the full set of findings of this article and the accompanying discussion.

Sprint interval and moderate-intensity continuous training have equal benefits on aerobic capacity, insulin sensitivity, muscle capillarisation and endothelial eNOS/NAD(P)Hoxidase protein ratio in obese men

Key points: Skeletal muscle capillary density and vasoreactivity are reduced in obesity, due to reduced nitric oxide bioavailability. Sprint interval training (SIT) has been proposed as a time efficient alternative to moderate-intensity continuous training (MICT), but its effect on the skeletal muscle microvasculature has not been studied in obese individuals. We observed that SIT and MICT led to equal increases in capillarisation and endothelial eNOS content, while reducing endothelial NOX2 content in microvessels of young obese men. We conclude that SIT is equally effective at improving skeletal muscle capillarisation and endothelial enzyme balance, while being a time efficient alternative to traditional MICT. Sprint interval training (SIT) has been proposed as a time efficient alternative to moderate-intensity continuous training (MICT), leading to similar improvements in skeletal muscle capillary density and microvascular function in young healthy humans. In this study we made the first comparisons of the muscle microvascular response to SIT and MICT in an obese population. Sixteen young obese men (age 25 ± 1 years, BMI 34.8 ± 0.9 kg m-2) were randomly assigned to 4 weeks of MICT (40-60 min cycling at ∼65% V˙O2 peak , 5 times per week) or constant load SIT (4-7 constant workload intervals of 200% Wmax 3 times per week). Muscle biopsies were taken before and after training from the m. vastus lateralis to measure muscle microvascular endothelial eNOS content, eNOS serine1177 phosphorylation, NOX2 content and capillarisation using quantitative immunofluorescence microscopy. Maximal aerobic capacity (V˙O2 peak ), whole body insulin sensitivity and arterial stiffness were also assessed. SIT and MICT increased skeletal muscle microvascular eNOS content and eNOS ser1177 phosphorylation in terminal arterioles and capillaries (P < 0.05), but the latter effect was eliminated when normalised to eNOS content (P = 0.217). SIT and MICT also reduced microvascular endothelial NOX2 content (P < 0.05) and both increased capillary density and capillary-fibre perimeter exchange index (P < 0.05). In parallel, SIT and MICT increased V˙O2 peak (P < 0.05) and whole body insulin sensitivity (P < 0.05), and reduced central artery stiffness (P < 0.05). As no significant differences were observed between SIT and MICT it is concluded that SIT is a time efficient alternative to MICT to improve aerobic capacity, insulin sensitivity and muscle capillarisation and endothelial eNOS/NAD(P)Hoxidase protein ratio in young obese men.

A review on artificial intelligence based load demand forecasting techniques for smart grid and buildings

Electrical load forecasting plays a vital role in order to achieve the concept of next generation power system such as smart grid, efficient energy management and better power system planning. As a result, high forecast accuracy is required for multiple time horizons that are associated with regulation, dispatching, scheduling and unit commitment of power grid. Artificial Intelligence (AI) based techniques are being developed and deployed worldwide in on Varity of applications, because of its superior capability to handle the complex input and output relationship. This paper provides the comprehensive and systematic literature review of Artificial Intelligence based short term load forecasting techniques. The major objective of this study is to review, identify, evaluate and analyze the performance of Artificial Intelligence (AI) based load forecast models and research gaps. The accuracy of ANN based forecast model is found to be dependent on number of parameters such as forecast model architecture, input combination, activation functions and training algorithm of the network and other exogenous variables affecting on forecast model inputs. Published literature presented in this paper show the potential of AI techniques for effective load forecasting in order to achieve the concept of smart grid and buildings.

The combination of plyometric and balance training improves sprint and shuttle run performances more often than plyometric-only training with children

Because balance is not fully developed in children and studies have shown functional improvements with balance only training studies, a combination of plyometric and balance activities might enhance static balance, dynamic balance, and power. The objective of this study was to compare the effectiveness of plyometric only (PLYO) with balance and plyometric (COMBINED) training on balance and power measures in children. Before and after an 8-week training period, testing assessed lower-body strength (1 repetition maximum leg press), power (horizontal and vertical jumps, triple hop for distance, reactive strength, and leg stiffness), running speed (10-m and 30-m sprint), static and dynamic balance (Standing Stork Test and Star Excursion Balance Test), and agility (shuttle run). Subjects were randomly divided into 2 training groups (PLYO [n = 14] and COMBINED [n = 14]) and a control group (n = 12). Results based on magnitude-based inferences and precision of estimation indicated that the COMBINED training group was considered likely to be superior to the PLYO group in leg stiffness (d = 0.69, 91% likely), 10-m sprint (d = 0.57, 84% likely), and shuttle run (d = 0.52, 80% likely). The difference between the groups was unclear in 8 of the 11 dependent variables. COMBINED training enhanced activities such as 10-m sprints and shuttle runs to a greater degree. COMBINED training could be an important consideration for reducing the high velocity impacts of PLYO training. This reduction in stretch-shortening cycle stress on neuromuscular system with the replacement of balance and landing exercises might help to alleviate the overtraining effects of excessive repetitive high load activities.