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Novel wearable near‐infrared spectroscopy devices allow for a better understanding of muscle oxygenation kinetics during exercise. A muscle oxygen saturation (SmO 2 ) plateau is often applied in the scientific literature, but clear criteria for its definition remain unestablished to date. The aim of this study was to develop criteria allowing for definition of SmO 2 plateaus. Multiple variables associated with physiological plateaus during exercise were assessed to develop a framework for an SmO 2 plateau. Subsequently, the existence of an SmO 2 plateau during 3 min all‐out cycling trials (critical oxygenation plateau) was tested in different conditions of oxygen availability (i.e., normoxia and hypoxia) in vastus lateralis and triceps brachii among 30 endurance athletes. Plateau determination methods based on a threshold of change of ±5 arbitrary units (a.u.) of SmO 2 and expert visual assessment showed almost perfect agreement. However, a threshold of 10 a.u. yielded high SmO 2 variability associated with a large number of possibly false‐positive detections. Conversely, relative changes (thresholds of 5% and 10%) did not align with other methods, corresponding to low absolute changes, limiting their applicability. The inter‐rater agreement between individual visual assessments exhibited a higher reliability among expert versus non‐expert raters. The determination of an SmO 2 plateau depends on the applied methodology. Overall, a critical oxygenation plateau was observed in the vastus lateralis in both normoxia and hypoxia in >90% of cases. The results of this study allow recommendation either for the use of a threshold of change corresponding to 5 a.u. of SmO 2 or expert visual assessment, using 30 s segments. What is the central question of this study? What is the muscle oxygen saturation plateau, and how should it be defined? What is the main finding and its importance? The determination of the muscle oxygen saturation plateau depends on the methodological approach applied. This plateau can be determined effectively using a threshold of change corresponding to 5 arbitrary units of percentage muscle oxygen saturation or expert visual assessment. Application of the recommended criteria, along with transparent reporting, might enhance the rigour of studies examining muscle oxygenation kinetics.

New Findings What is the central question of this study? Does prescribing exercise intensity using physiological thresholds create a more homogeneous exercise stimulus than using traditional intensity anchors? What is the main finding and its importance? Prescribing exercise using physiological thresholds, notably critical power, reduced the variability in exercise tolerance and acute metabolic responses. At higher intensities, approaching or exceeding the transition from heavy to severe intensity exercise, the imprecision of using fixed %V̇O2max ${\\dot V_{{{\\rm{O}}_{\\rm{2}}}{\\rm{max}}}$  as an intensity anchor becomes amplified. The objective of this study was to determine whether the variability in exercise tolerance and physiological responses is lower when exercise is prescribed relative to physiological thresholds (THR) compared to traditional intensity anchors (TRAD). Ten individuals completed a series of maximal exercise tests and a series of moderate (MOD), heavy (HVY) and severe intensity (HIIT) exercise bouts prescribed using THR intensity anchors (critical power and gas exchange threshold) and TRAD intensity anchors (maximum oxygen uptake; V̇O2max ${\\dot V_{{{\\rm{O}}_{\\rm{2}}}{\\rm{max}}}$ ). There were no differences in exercise tolerance or acute response variability between MODTHR and MODTRAD. All individuals completed HVYTHR but only 30% completed HVYTRAD. Compared to HVYTHR, where work rates were all below critical power, work rates in HVYTRAD exceeded critical power in 70% of individuals. There was, however, no difference in acute response variability between HVYTHR and HVYTRAD. All individuals completed HIITTHR but only 20% completed HIITTRAD. The variability in peak (F = 0.274) and average (F = 0.318) blood lactate responses was lower in HIITTHR compared to HIITTRAD. The variability in W′ depletion (the finite work capacity above critical power) after the final interval bout was lower in HIITTHR compared to HIITTRAD (F = 0.305). Using physiological thresholds to prescribe exercise intensity reduced the heterogeneity in exercise tolerance and physiological responses to exercise spanning the boundary between the heavy and severe intensity domains. To increase the precision of exercise intensity prescription, it is recommended that, where possible, physiological thresholds are used in place of V̇O2max ${\\dot V_{{{\\rm{O}}_{\\rm{2}}}{\\rm{max}}}$ .

Dissimilar metal welded (DMW) joint plays a crucial role in constructing and maintaining ultra-supercritical (USC) nuclear power plants while presenting noteworthy environmental implications. This research examines different welding techniques utilized in DMWJ, specifically emphasizing materials such as P91. The study investigates the mechanical properties of these materials, the impact of alloying elements, the notable difficulties encountered with industrial materials, and the concept of buttering. The USC nuclear power plants necessitate welding procedures appropriate for the fusion of diverse metal alloys. Frequently employed methodologies encompass shielded metal arc welding (SMAW), gas tungsten arc welding (GTAW), gas metal arc welding (GMAW), and flux-cored arc welding (FCAW). Every individual process possesses distinct advantages and limitations, and the choice of process is contingent upon various factors, including joint configuration, material properties, and the desired weld quality. The steel alloy known as P91, which possesses high strength and resistance to creep, is extensively employed in advanced ultra-supercritical (AUSC) power plants. P91 demonstrates exceptional mechanical characteristics, encompassing elevated-temperature strength, commendable thermal conductivity, and notable resistance against corrosion and oxidation. The presence of alloying elements, namely chromium, molybdenum, and vanadium, in P91, is responsible for its improved characteristics and appropriateness for utilization in (AUSC) power plant applications. Nevertheless, the utilization of industrial materials in DMW joint is accompanied by many noteworthy concerns, such as the propensity for stress corrosion cracking (SCC), hydrogen embrittlement, and creep deformation under high temperatures. The challenges mentioned above require meticulous material selection, process optimization, and rigorous quality control measures to guarantee the dependability and sustained effectiveness of DMW joint. To tackle these concerns, a commonly utilized approach referred to as buttering is frequently employed. When forming DMW joint in nuclear facilities, it is customary to place a buttering coating on ferritic steel. This facilitates the connection between pressure vessel components of ferritic steel and pipes of austenitic stainless steel. The primary difficulty in DMW joint manufacturing is in mitigating the significant disparity in material characteristics resulting from carbon migration and metallurgical alterations along the fusion interface between ferritic steel and austenitic stainless steel. The process of buttering entails the application of a compatible filler material onto the base metal before the deposition of the desired weld metal. The intermediate layer serves as a mediator, enhancing the metallurgical compatibility, diminishing the probability of fracture, and enhancing the overall integrity of the joint. Buttering is still a new research area with a wide scenario of scope in terms of development, which could revolutionize developing high-temperature. These long-term sustainable joints could serve under critical conditions like AUSC power plants and reduce CO 2 emissions by increasing the overall efficiencies of the systems.

Current research on the interference of GNSS (Global Navigation Satellite System) array antennas focuses on the single interference effect and the improvement of interference hardware capability, while the multi-degree-of-freedom (DOF) interference model and mechanism remain to be fully studied. Aiming at this problem, this paper analyzes the preconditions for the definition of anti-jamming degrees of freedom and the characteristics of super-DOF interference through formula derivation and simulation. First, by analyzing the influence of the number of interfering signals on the angular resolution, the prerequisite of the definition of anti-interference degrees of freedom in the airspace is proposed. Second, the definition of anti-interference degrees of freedom is used to calculate the change rule of the critical power of the interference under different numbers of interfering signals. Finally, the influence of super-DOF interference on the array antenna is analyzed. The results show that the prerequisite for the anti-interference freedom of the array antenna is that the distribution interval of the interfering signal is greater than 15°, taking a four-array element uniform circular array antenna as an example. The critical interference power of the array antenna decreases by about 15 dB when the number of interfering signals exceeds the degrees of freedom of the array antenna’s interference immunity, provided that the interference resolution is satisfied. The conclusions of this paper give the critical power change rule of multi-DOF interference and the effect of super-DOF interference, as well as the prerequisites for the setting of interference signals, which can be used, for example, in the deployment of distributed interference sources and the development of anti-jamming algorithms.

PurposeThis study longitudinally examined the interchangeable use of critical power (CP), the maximal lactate steady state (MLSS) and the respiratory compensation point (RCP) (i.e., whole-body thresholds), and breakpoints in muscle deoxygenation (m[HHb]BP) and muscle activity (iEMGBP) (i.e., local thresholds).MethodsTwenty-one participants were tested on two timepoints (T1 and T2) with a 4-week period (study 1: 10 women, age = 27 ± 3 years, V˙O2peak = 43.2 ± 7.3 mL min−1kg−1) or a 12-week period (study 2: 11 men, age = 25 ± 4 years, V˙O2peak = 47.7 ± 5.9 mL min−1 kg−1) in between. The test battery included one ramp incremental test (to determine RCP, m[HHb]BP and iEMGBP) and a series of (sub)maximal constant load tests (to determine CP and MLSS). All thresholds were expressed as oxygen uptake (V˙O2) and equivalent power output (PO) for comparison.ResultsNone of the thresholds were significantly different in study 1 (V˙O2: P = 0.143, PO: P = 0.281), but differences between whole-body and local thresholds were observed in study 2 (V˙O2: P < 0.001, PO: P = 0.024). Whole-body thresholds showed better 4-week test–retest reliability (TEM = 88–125 mL min−1 or 6–10 W, ICC = 0.94–0.98) compared to local thresholds (TEM = 189–195 mL min−1 or 15–18 W, ICC = 0.58–0.89). All five thresholds were strongly associated at T1 and T2 (r = 0.75–0.99), but their changes from T1 to T2 were mostly uncorrelated (r = − 0.41–0.83).ConclusionWhole-body thresholds (CP/MLSS/RCP) showed a close and consistent coherence taking into account a 3–6%-bandwidth of typical variation. In contrast, local thresholds (m[HHb]BP/iEMGBP) were characterized by higher variability and did not consistently coincide with the whole-body thresholds. In addition, we found that most thresholds evolved independently of each other over time. Together, these results do not justify the interchangeable use of whole-body and local exercise thresholds in practice.

Cyber intrusions into critical infrastructure inflict economic and physical damage. Extensive research is needed to identify and mitigate intrusions in power grid infrastructure. The modern solution is to use a data science time-series approach to identify the intrusion based on the electric grid data collected from the sensors. This paper addresses the new vision of the data science time-series modelling approach to integrate it with the existing power system security system. In this paper, the Advanced Autoregressive Moving Average (A AR.MA) model is designed to detect the possible intrusion of the given data set. An attack forecast is a model to predict possible cyber intrusions using real-time data input from sensors. By investigating the statistical properties of the sensors' data set. intrusion detection is possible with a high accuracy of about 90%. Using AAR.MA, the operators have the benefit of an effective alert system to adjust their configuration and other resource allocation to tackle intrusions with low impact. MATLAB software is used to monitor the TREE 9-bus and IEEE 33-bus test systems against possible cyber-attacks using the proposed AARMA model.

PurposeBased on the critical power (Pc or critical force; Fc) concept, a recent mathematical model formalised the proportional link between the decrease in maximal capacities during fatiguing exercises and the amount of impulse accumulated above Fc. This study aimed to provide experimental support to this mathematical model of muscle fatigability in the severe domain through testing (i) the model identifiability using non-exhausting tests and (ii) the model ability to predict time to exhaustion (tlim) and maximal force (Fmax) decrease.MethodsThe model was tested on eight participants using electrically stimulated adductor pollicis muscle force. The Fmax was recorded every 15 s for all tests, including five constant tests to estimate the initial maximal force (Fi), Fc, and a time constant (τ). The model’s parameters were used to compare the predicted and observed tlim values of the incremental ramp test and Fmax(t) of the sine test.ResultsThe results showed that the model accurately estimated Fi, Fc, and τ (CI95% = 2.7%Fi and 9.1 s for Fc and τ, respectively; median adjusted r2 = 0.96) and predicted tlim and Fmax with low systematic and random errors (11 ± 20% and − 1.8 ± 7.7%Fi, respectively).ConclusionThis study revealed the potential applications of a novel mathematical formalisation that encompasses previous research on the critical power concept. The results indicated that the model’s parameters can be determined from non-exhaustive tests, as long as maximal capacities are regularly assessed. With these parameters, the evolution of maximal capacities (i.e. fatigability) at any point during a known exercise and the time to exhaustion can be accurately predicted.

Specifically, in healthy men and women who completed multiple exhausting cycling tests (graded exercise test, series of constant-power tests) to define GET, CP and W′, these parameters and also V̇O2max${\\dot V_{{{\\rm{O}}_2}\\max }}$ (i.e., at defined percentages of V̇O2max${\\dot V_{{{\\rm{O}}_2}\\max }}$ ) were utilized to anchor separate moderate- (MOD), heavy- and severe-intensity criterion exercise bouts. (2023) demonstrate that prescribing exercise relative to CP can prevent this occurrence and, even for supra-CP exercise, reduce inter-subject response variability for key physiological indices. (2023), it is also important to note that, by registering severe-intensity exercise bouts to CP and thereby lowering inter-subject variability for W′ depletion, it would be expected that greater homogeneity would be achieved across participants for intramyocyte perturbations (e.g., ∆[PCr], [Pi], [ADPfree], [H+], [glycogen]; Jones et al., 2008) in addition to, of course, improved ability to predict exercise tolerance.

Purpose Endurance training improves running performance in distances where oxidative phosphorylation (OXPHOS) is the main ATP source. Here, a dynamic computer model is used to assess possible biochemical mechanisms underlying this improvement. Methods The dynamic computer model is based on the “P i double-threshold” mechanism of muscle fatigue, according to which the additional ATP usage appears when (1) inorganic phosphate (P i ) exceeds a critical value (Pi crit ); (2) exercise is terminated because of fatigue, when P i reaches a peak value (Pi peak ); (3) the P i increase and additional ATP usage increase mutually stimulate each other. Results The endurance-training-induced increase in oxidative phosphorylation (OXPHOS) activity attenuates the reaching of Pi peak by P i (and thus of V ˙ O 2max by V ˙ O 2 ) at increased power output. This in turn allows a greater work intensity, and thus higher speed, to be achieved before exercise is terminated because of fatigue at the end of the 1500 m run. Thus, identical total work is performed in a shorter time. Probably, endurance training also lowers Pi peak , which improves the homeostasis of “bioenergetic” muscle metabolites: ADP, PCr, P i and H + ions. Conclusions The present dynamic computer model generates clear predictions of metabolic changes that limit performance during 1500 m running. It contributes to our mechanistic understanding of training-induced improvement in running performance and stimulates further physiological experimental studies.