High-intensity interval resistance training (HIIRT) improves liver gluconeogenesis from lactate in Swiss mice

High-intensity physical exercise favors anaerobic glycolysis and increases lactatemia. Lactate is converted back to glucose in the liver, so that the lactate threshold, an indicator of physical performance, must be related to the gluconeogenic capacity of the liver. This research assessed the effect of a high-intensity interval resistance training (HIIRT) on liver gluconeogenesis from lactate. Swiss mice were trained (groups T) on vertical ladder with overload of 90% of their maximal load. Control animals remained untrained (groups C0 and C8). In situ liver perfusion with lactate and adrenaline was performed in rested mice after six hours of food deprivation. There were larger outputs of glucose (T6 71.90%, T8 54.53%) and pyruvate (T8 129.28%) (representative values for 4 mM lactate) in the groups trained for six or eight weeks (T6 and T8), and of glucose in the presence of adrenaline in group T8 (280%). The content of PEPCK, an important regulatory enzyme of the gluconeogenic pathway, was 69.13% higher in group T8 than in the age-matched untrained animals (C8). HIIRT augmented liver gluconeogenesis from lactate and this might improve the lactate threshold. Bullet points: The liver metabolizes lactate from muscle into glucose. Physical training may enhance the gluconeogenic capacity of the liver. As lactate clearance by the liver improves, lactate threshold is displaced to higher exercise intensities.

PROBABILISTIC ANALYSIS OF THE MAXIMAL LOAD OF INDUSTRIAL MACHINES

This study describes the statistical analysis of peak forces of industrial washing machines. The data source comes from twelve different machines. The measurements are done using a force gauge installed in places for fastening screws. A new software based on LabView has been developed to gauge the acting forces. To determine extreme force values, various probability distributions are applied. Furthermore, a convex combination of lognormal distribution is used in more complicated cases. The parameters of the lognormal mixtures are determined using modified an Expectation-maximization algorithm. Finally, the achieved results are interpreted with regard to the engineering design and to the operating reliability.

The Maximum Flywheel Load: A Novel Index to Monitor Loading Intensity of Flywheel Devices

Background: The main aim of this study was (1) to find an index to monitor the loading intensity of flywheel resistance training, and (2) to study the differences in the relative intensity workload spectrum between the FW-load and ISO-load. Methods: twenty-one males participated in the study. Subjects executed an incremental loading test in the squat exercise using a Smith machine (ISO-load) or a flywheel device (FW-load). We studied different association models between speed, power, acceleration, and force, and each moment of inertia was used to find an index for FW-load. In addition, we tested the differences between relative workloads among load conditions using a two-way repeated-measures test. Results: the highest r2 was observed using a logarithmic fitting model between the mean angular acceleration and moment of inertia. The intersection with the x-axis resulted in an index (maximum flywheel load, MFL) that represents a theoretical individual maximal load that can be used. The ISO-load showed greater speed, acceleration, and power outcomes at any relative workload (%MFL vs. % maximum repetition). However, from 45% of the relative workload, FW-load showed higher vertical forces. Conclusions: MFL can be easily computed using a logarithmic model between the mean angular acceleration and moment of inertia to characterize the maximum theoretical loading intensity in the flywheel squat.

Moderately trained male football players, compared to sedentary male adults, exhibit anatomical but not functional cardiac remodelling, a cross-sectional study

Background Elite athletes have been the subject of great interest, but athletes at an intermediate level of physical activity have received less attention in respect to the presence of cardiac enlargement and/or hypertrophy. We hypothesized that playing football, often defined as demanding less endurance components than running or cycling, would still induce remodelling similar to sports with a dominating endurance component. Methods 23 male football players, age 25+/− 3.9 yrs. underwent exercise testing, 2D- and 3D- echocardiography and cardiac magnetic resonance (CMR). The results were compared with a control group of engineering students of similar age. The athletes exercised 12 h/week and the control subjects 1 h/week, p < 0.001. Results The football players achieved a significantly higher maximal load at the exercise test (380 W vs 300 W, p < 0.001) as well as higher calculated maximal oxygen consumption, (49.7 vs 37.4 mL x kg− 1 x min− 1, p < 0.001) compared to the sedentary group. All left ventricular (LV) volumes assessed by 3DEcho and CMR, as well as CMR left atrial (LA) volume were significantly higher in the athletes (3D-LVEDV 200 vs 154 mL, CMR-LVEDV 229 vs 185 mL, CMR-LA volume 100 vs 89 mL, p < 0.001, p = 0.002 and p = 0.009 respectively). LVEF and RVEF, LV strain by CMR or by echo did not differentiate athletes from sedentary participants. Right ventricular (RV) longitudinal strain, LA and right atrial (RA) strain by CMR all showed similar results in the two groups. Conclusion Moderately trained intermediate level football players showed anatomical but not functional cardiac remodelling compared to sedentary males.

Biomechanical Performance of BoneHelix® Compared with Elastic Stable Intramedullary Nailing (ESIN) in a Pediatric Tibia Fracture Model

Tibial shaft fractures are common injuries in the pediatric and adolescent populations. Elastic stable intramedullary nailing (ESIN) is the treatment of choice for cases that require surgical stabilization. A new intramedullary device, BoneHelix® (BH), may be an alternative for use with fractures that cannot be satisfactorily stabilized with ESIN. This study aimed to assess the biomechanical performance of BH compared with ESIN in a porcine tibia fracture model, observing cyclic fatigue and load to failure. Computed tomography was used to monitor the implant position and to rule out unintended damage. No implant or bone failure occurred during the fatigue testing. An increase in the cumulative plastic displacement was observed in both test groups over the loading cycles applied. Both implant–bone constructs displayed a trend toward closure of the osteotomy gap. During the load-to-failure test, the average loads at failure in specimens instrumented with ESIN and BH were 5364 N (±723) and 4350 N (±893), respectively, which were not statistically significant (p = 0.11). The values of both groups were two to three times higher than the estimated maximal load (2000 N) during physiological weight bearing. The biomechanical results thus indicate equivalent performance and stability by the implants tested.

Analysis of the Electroconsolidation Process of Fine-Dispersed Structures Out of Hot Pressed Al2O3–WC Nanopowders

Fabrication of alumina–tungsten carbide nanocomposite was investigated. Characteristics of the densification and sintering were analyzed considering both the nano-size particle starting powders and the processing stages. Different heating rates were generated during densification and consolidation with a maximal load was applied only after a temperature of 1000 °C was reached. Due to the varying dominance of different physical processes affecting the grains, appropriate heating rates and pressure at different stages ensured that a structure with submicron grains was obtained. With directly applied alternating current, it was found that the proportion Al2O3 (50 wt.%)–WC provided the highest fracture toughness, and a sintering temperature above 1600 °C was found to be disadvantageous. High heating rates and a short sintering time enabled the process to be completed in 12 min, saving energy and time.

Influence of Kite Characteristics on Propulsive Power Applied to Ship Auxiliary Propulsion

A Design of Experiment method was applied combined with a performance prediction program to assess the influence of four design parameters on the propulsive capacity of kites used as auxiliary propulsion for merchant vessels. Those parameters are the lift coefficient, the lift to drag ratio or drag angle, the maximal load bearable by the kite and the ratio of the tether length on the square root of the kite area. These parameters are independent from the kite area and, therefore, they could be used with various kite ranges and types. The maximum wing load parameter is the one that shows the most influence on the propulsive force. Over 50% of the gains obtained through this study are directly attributable to it. Then the ratio of the tether length on the square root of the kite area comes as the second greatest influence factor for true wind angles above 70°. While the drag angle is more influential for the narrower angles. In fact, the most substantial gains are made upwind.

Intraocular pressure fluctuation during resistance exercise

ObjectiveTo evaluate the effect of weightlifting (leg press) on intraocular pressure (IOP).DesignProspective cohort study.SubjectsA total of 24 participants met the inclusion criteria and completed the study procedures. Participants had an average age of 22.7±2.7 years and included nine women. The mean baseline IOP was 13.9 mm Hg (SD=2.4) with an average body mass index of 24.5 (SD= 3.1).MethodsThe maximum load for a single lift was found for each participant. Participants then performed three leg press regimens: one repetition using 95% of maximal load (1RM), six repetitions using 75% of maximal load (6RM) and isometric push against a weight much heavier than maximal load (ISO).Main outcome measureIOP was measured pre-exercise, during and immediately following the exercise using an iCare TA01i rebound tonometer. Blood pressure and HR were being monitored continuously during the lift. Optical coherence tomography images were obtained pre and postexercise session.ResultsThe average maximum weight lifted by our participants was 331.9 Kg (SD=97.3). Transient increased IOP was observed across the 1RM, 6RM and ISO exercises with an average increase in 26.4 mm Hg (23.7 mm Hg to 28.7 mm Hg) to reach an average max IOP of 40.7 mm Hg (27.8 mm Hg to 54.2 mm Hg), with an absolute maximum of 70 mm Hg in one participant.ConclusionsThere is a transient and dramatic fluctuation in IOP with resistance training. This coupled with regular exposure to resistance training is potentially a significant risk factor for glaucoma. It should be noted that this study has been carried out in a healthy young population, and, thus, the external validity of these results in glaucoma participants requires further investigation.

Deep Learning-Based Approaches to Optimize the Electricity Contract Capacity Problem for Commercial Customers

The electricity tariffs available to customers in Poland depend on the connection voltage level and contracted capacity, which reflect the customer demand profile. Therefore, before connecting to the power grid, each consumer declares the demand for maximum power. This amount, referred to as the contracted capacity, is used by the electricity provider to assign the proper connection type to the power grid, including the size of the security breaker. Maximum power is also the basis for calculating fixed charges for electricity consumption, which is controlled and metered through peak meters. If the peak demand exceeds the contracted capacity, a penalty charge is applied to the exceeded amount, which is up to ten times the basic rate. In this article, we present several solutions for entrepreneurs based on the implementation of two-stage and deep learning approaches to predict maximal load values and the moments of exceeding the contracted capacity in the short term, i.e., up to one month ahead. The forecast is further used to optimize the capacity volume to be contracted in the following month to minimize network charge for exceeding the contracted level. As confirmed experimentally with two datasets, the application of a multiple output forecast artificial neural network model and a genetic algorithm (two-stage approach) for load optimization delivers significant benefits to customers. As an alternative, the same benefit is delivered with a deep learning architecture (hybrid approach) to predict the maximal capacity demands and, simultaneously, to determine the optimal capacity contract.

Impact of Super Heavy Load Vehicles on Transportation Infrastructure: Economic Aspects

Sometimes, there is a need to transport very heavy equipment, so heavy that the resulting load is several times larger than the maximal load that the corresponding road segment was designed to withstand. Such super heavy load vehicles decrease the remaining service life of the road segment, and sometimes even make the segment unusable and needing repairs. In both cases, the need for earlier-than-expected repairs means additional costs. It is therefore desirable to estimate the expected value of this additional cost. In locations where the owner of the super heavy load vehicle pays for the vehicle passage, this is necessary to decide how much to charge the owner. In other locations, where the agreement is that the cost of additional repairs comes from the additional taxes that the vehicle owners pay, such an estimate is needed to the road owners -- e.g., to the county or to the state -- so as to select the route for which the expected additional cost of repairs is the smallest.