Dietary intake, energy availability, and power in men collegiate gymnasts.

Introduction: The purpose was to examine the prevalence of low energy availability (LEA), explore dietary behaviors in men collegiate gymnasts (n = 14), and investigate the relationships between energy availability (EA), body composition, and plyometric performance. Methods: Body composition was measured using air displacement plethysmography. Lower- and upper-body peak power (PWRpeak) and modified reactive strength index (RSImod) were calculated from countermovement jump (CMJ) and plyometric push-up (PP) assessments. Energy expenditure was tracked over 3 days, while daily energy and macronutrient intake were recorded. EA was calculated and used to categorize athletes into LEA and non-LEA groups. Pearson correlation coefficients were used to examine relationships between EA, body composition, and performance metrics. Results: 85.7% of athletes (n = 12) exhibited LEA (20.98 ± 5.2 kcals/kg FFM), with non-LEA athletes (n = 2) marginally surpassing the <30 kcal/kg of fat-free mass (FFM) threshold (30.58 ± 0.2 kcals/kg FFM). The cohort (n = 14) consumed insufficient energy (30.5 ± 4.5 kcal/kg/day) and carbohydrates (3.7 ± 1.1 g/kg/day), resulting in LEA (22.36 ± 5.9 kcal/kg/FFM). EA was not correlated with body composition or performance metrics. Discussion: A high prevalence of LEA may exist in men gymnasts, largely due to a low relative energy and carbohydrate intake.

Changes in the force-time curve during a repeat power ability assessment using loaded countermovement jumps.

Background: Repeat power ability (RPA) assessments traditionally use discrete variables, such as peak power output, to quantify the change in performance across a series of jumps. Rather than using a discrete variable, the analysis of the entire force-time curve may provide additional insight into RPA performance. The aims of this study were to (1) analyse changes in the force-time curve recorded during an RPA assessment using statistical parametric mapping (SPM) and (2) compare the differences in the force-time curve between participants with low and high RPA scores, as quantified by traditional analysis. Materials and Methods: Eleven well-trained field hockey players performed an RPA assessment consisting of 20 loaded countermovement jumps with a 30% one repetition maximum half squat load (LCMJ20). Mean force-time series data was normalized to 100% of the movement duration and analysed using SPM. Peak power output for each jump was also derived from the force-time data and a percent decrement score calculated for jumps 2 to 19 (RPA%dec). An SPM one-way ANOVA with significance accepted at α = 0.05, was used to identify the change in the force-time curve over three distinct series of jumps across the LCMJ20 (series 1 = jumps 2-5, series 2 = jumps 9-12 and series 3 = jumps 16-19). A secondary analysis, using an independent T-test with significance accepted at p < 0.001, was also used to identify differences in the force-time curve between participants with low and high RPA%dec. Results: Propulsive forces were significantly lower (p < 0.001) between 74-98% of the movement compared to 0-73% for changes recorded during the LCMJ20. Post hoc analysis identified the greatest differences to occur between jump series 1 and jump series 2 (p < 0.001) at 70-98% of the movement and between jump series 1 and jump series 3 (p < 0.001) at 86-99% of the movement. No significant differences were found between jump series 2 and jump series 3. Significant differences (p < 0.001) in both the braking phase at 44-48% of the jump and the propulsive phase at 74-94% of the jump were identified when participants were classified based on low or high RPA%dec scores (with low scores representing an enhanced ability to maintain peak power output than high scores). Conclusion: A reduction in force during the late propulsive phase is evident as the LCMJ20 progresses. SPM analysis provides refined insight into where changes in the force-time curve occur during performance of the LCMJ20. Participants with the lower RPA%dec scores displayed both larger braking and propulsive forces across the LCMJ20 assessment.

Performance analysis of partially shaded high-efficiency mono PERC/mono crystalline PV module under indoor and environmental conditions.

The ever-increasing demand for sustainable energy has drawn attention towards photovoltaic efficiency and reliability. In this context, the shading and associated hotpot degradation within PV modules has become an important area of research and development. The experimental approach of this paper aims to investigate single cell shading in high efficiency monocrystalline silicon PV PERC modules. Prior to the outdoor experiment, the PV module underwent experimental testing under STC to determine variation in electrical and thermal behaviour due to partial shading. The indoor experiments are performed using Sun-simulator and the I-V and P-V curves are analysed. Further, the outdoor experiments were performed under realistic conditions. In both cases, results showed that during 40-60% shading in single cell leads to critical shading scenario causing significant drop in power output in comparison with their unshaded conditions. The maximum power loss of 36.34% and 42% is recorded for indoor and outdoor experiments. The outdoor experiments recorded hotspot temperature of 85-90.1 °C under respective 40% and 60% critical shading scenarios. The efficiency recorded in the time interval of 11:00:00 and 11:30:00 was highest for the solar radiations between 940 and 990 W/m2. The maximum drop in efficiency is recorded from noon till 13:30:00 time of the day. Development of hotspot is directly related to the failure or malfunction of protecting system. Hence the importance of type of PV technology, amount of shading, and critical shading scenario is presented in the study. This study is important for researcher and manufacture to consider single cell shading in PV technology.

The effect of caffeine chewing gum on muscle performance and fatigue after severe-intensity exercise: isometric vs. dynamic assessments in trained cyclists.

This study investigated the effect of caffeinated chewing gum (GUMCAF) on muscle fatigue (isometric vs. dynamic) after severe-intensity cycling bouts. Fifteen trained male cyclists participated in four visits. Each visit involved two severe-intensity cycling bouts (Δ1 and Δ2) lasting 6 min, separated by a 5-min recovery period. Muscle fatigue was assessed by isometric maximal voluntary knee extension contraction (IMVC) with twitch interpolation technique and dynamically by 7 s all-out cycling sprints. Assessments were performed before GUMCAF (Pre-GUM) and after the cycling bouts (Post-Exercise). GUMCAF and placebo gum (GUMPLA) were administered in a randomized double-blind procedure with participants receiving each gum type (GUMCAF and GUMPLA) during two separate visits. The results showed no significant interaction between gum types and time for the isometric and dynamic measurements (p > 0.05). The percentage change in performance from Pre-GUM to Post-Exercise showed no significant difference between GUMCAF and GUMPLA for either the dynamic-derived TMAX (~ -17.8% and -15.1%, respectively; p = 0.551) or isometric IMVC (~ -12.3% and -17.7%, respectively; p = 0.091) measurements. Moderate to large correlations (r = 0.31-0.51) were found between changes in sprint maximal torque and maximal power output measurements and isometric force, for both gum conditions. GUMCAF was not effective in attenuating muscle force decline triggered by severe-intensity cycling exercises, as measured by both isometric and dynamic methods. The correlations between IMVC and cycling maximal torque and power output suggest caution when interpreting isometric force as a direct measure of fatigue during dynamic cycling exercises.

Efficient Permeable Monolithic Hybrid Tribo-Piezo-Electromagnetic Nanogenerator Based on Topological-Insulator-Composite.

Escalating energy demands of self-independent on-skin/wearable electronics impose challenges on corresponding power sources to offer greater power density, permeability, and stretchability. Here, a high-efficient breathable and stretchable monolithic hybrid triboelectric-piezoelectric-electromagnetic nanogenerator-based electronic skin (TPEG-skin) is reported via sandwiching a liquid metal mesh with two-layer topological insulator-piezoelectric polymer composite nanofibers. TPEG-skin concurrently extracts biomechanical energy (from body motions) and electromagnetic radiations (from adjacent appliances), operating as epidermal power sources and whole-body self-powered sensors. Topological insulators with conductive surface states supply notably enhanced triboelectric and piezoelectric effects, endowing TPEG-skin with a 288 V output voltage (10 N, 4 Hz), ∼3 times that of state-of-the-art devices. Liquid metal meshes serve as breathable electrodes and extract ambient electromagnetic pollution (±60 V, ±1.6 µA cm-2). TPEG-skin implements self-powered physiological and body motion monitoring and system-level human-machine interactions. This study provides compatible energy strategies for on-skin/wearable electronics with high power density, monolithic device integration, and multifunctionality.

Physiological and perceptual responses to sprint interval exercise using arm versus leg cycling ergometry.

Increases in power output and maximal oxygen consumption ( V ˙ O 2 max) occur in response to sprint interval exercise (SIE), but common use of "all-out" intensities presents a barrier for many adults. Furthermore, lower-body SIE is not feasible for all adults. We compared physiological and perceptual responses to supramaximal, but "non-all-out" SIE between leg and arm cycling exercise. Twenty-four active adults (mean â€‹± â€‹SD age: [25 â€‹± â€‹7] y; cycling V ˙ O 2 max: [39 â€‹± â€‹7] mL·kg-1·min-1) performed incremental exercise using leg (LCE) and arm cycle ergometry (ACE) to determine V ˙ O 2 max and maximal work capacity (Wmax). Subsequently, they performed four 20 â€‹s bouts of SIE at 130% Wmax on the LCE or ACE at cadence â€‹= â€‹120-130 â€‹rev/min, with 2 â€‹min recovery between intervals. Gas exchange data, heart rate (HR), blood lactate concentration (BLa), rating of perceived exertion (RPE), and affective valence were acquired. Data showed significantly lower (p â€‹< â€‹0.001) absolute mean ([1.24 â€‹± â€‹0.31] L·min-1 vs. [1.59 â€‹± â€‹0.34] L·min-1; d â€‹= â€‹1.08) and peak V ˙ O 2 ([1.79 â€‹± â€‹0.48] L·min-1 vs. [2.10 â€‹± â€‹0.44] L·min-1; d â€‹= â€‹0.70) with ACE versus LCE. However, ACE elicited significantly higher (p â€‹< â€‹0.001) relative mean ([62% â€‹± â€‹9%] V ˙ O 2 max vs. [57% â€‹± â€‹7%] V ˙ O 2 max, d â€‹= â€‹0.63) and peak V ˙ O 2 ([88% â€‹± â€‹10%] V ˙ O 2 max vs. [75% â€‹± â€‹10%] V ˙ O 2 max, d â€‹= â€‹1.33). Post-exercise BLa was significantly higher ([7.0 â€‹± â€‹1.7] mM vs. [5.7 â€‹± â€‹1.5] mM, p â€‹= â€‹0.024, d â€‹= â€‹0.83) for LCE versus ACE. There was no significant effect of modality on RPE or affective valence (p â€‹> â€‹0.42), and lowest affective valence recorded (2.0 â€‹± â€‹1.8) was considered "good to fairly good". Data show that non "all-out" ACE elicits lower absolute but higher relative HR and V ˙ O 2 compared to LCE. Less aversive perceptual responses could make this non-all-out modality feasible for inactive adults.

Impact of Stiffness of Quadriceps on the Pedaling Rate of Maximal Cycling.

Propulsive power is one of the factors that determine the performance of sprint cycling. Pedaling rate is related to power output, and stiffness is associated with improving performance in athletic tasks. PURPOSE: to investigate the relationship between musculoarticular stiffness and pedaling rate. METHODS: twenty-two healthy, untrained male volunteers (19 ± 2 years, 175 ± 6 cm, 74 ± 16 kg) were divided into two groups after their musculoarticular (MA) stiffness was tested, and these groups were the stiffness group (SG) and compliant group (CG). A 6-s maximal cycling test was conducted in four cycling modes, which were levels 5 and 10 air-resistance, and levels 3 and 7 magnetic-resistance. Peak and average cadence, peak power output (POpeak), crank force (CFpeak), peak rate of crank force development (RCFD), and the angle of peak crank force were collected. The significance of differences between the two groups for these variables was assessed using an independent samples t-test. Pearson product-moment correlations were calculated to analyze the relationship between MA stiffness and each performance variable. RESULTS: the SG had significantly higher peak cadence and average cadence at level 3 magnetic-resistance, peak crank force, and peak power output at level 10 air-resistance, peak rate of crank force development at levels 5 air-resistance, 10 air-resistance, and 3 magnetic-resistance (p < 0.05). MA stiffness was significantly correlated with average cadence at levels 5 and 10 air-resistance, peak crank force in all 4 modes, and RCFD and peak power output at level 10 air-resistance. There were no significant relationships between MA stiffness and the angle of peak crank force in each cycling mode. CONCLUSION: results indicate that participants with relatively higher MA stiffness seemed to have a higher pedaling rate during a 6-s sprint cycling in these conditions. They also performed a superior crank force and rate of crank force development, producing greater power output when sprint cycling. Optimizing cycling resistance or gear ratio to enhance both RCFD and musculotendinous stiffness may be crucial for improving sprint cycling performance.

Investigation of low-GWP working fluids as substitutes for R245fa in organic Rankine cycle application.

This study presents a thermo-economic assessment of three low-global-warming-potential (GWP) substitutes, R1233zd(E), R1234ze(Z) and R1234ze(E), for R245fa used in organic Rankine cycle (ORC) systems, considering two models with different heat sources. The exhaust heat from a diesel generator is served as heat source of Model I, while the waste heat of exhaust and jacket cooling water are used as heat source of Model II. It is noted that the working pressure of R1234ze(E) is much higher than that of R1233zd(E), R1234ze(Z) and R245fa in a fixed evaporation-temperature range. Furthermore, the system using R1234ze(E) has the minimum net power output for Model I, while it turns into the maximum net power output for Model II. In addition, both R1234ze(Z) and R1233zd(E) can be used as good alternative working fluids for R245fa because R1234ze(Z), R1233zd(E) and R245fa have close working pressures, maximum net power outputs, and minimum levelized energy costs. Compared to Model I, LEC min of R1233ed(E) and R1234ze(Z) are reduced by 10.8 % and 9.9 % and PB min of R1233ed(E) and R1234ze(Z) are reduced by 11.5 % and 10.1 %, respectively, in Model II. However, R1233zd(E) has the highest minimum payback period for both Model I and Model II among the four working fluids investigated.

High-Performance Printed Ag2Se/PI Flexible Thermoelectric Film for Powering Wearable Electronics.

We report the magnificent thermoelectric properties of the n-type Ag2Se film printed onto a flexible polyimide (PI) substrate. The orthorhombic ß-Ag2Se phase of the processed Ag2Se film is confirmed from the X-ray diffractogram. Remarkably, the resulting Ag2Se/PI film exhibits outstanding thermoelectric properties, boasting maximum power factors of 1.4 and 2.1 mW/mK2 at 300 and 405 K, respectively. Furthermore, the flexibility of the Ag2Se/PI film remains intact even after undergoing 1500 bending cycles with no degradation observed in its thermoelectric performance. To demonstrate the practical application of our findings, a flexible thermoelectric prototype is constructed using the fabricated Ag2Se/PI films, which can harvest an impressive output voltage of 52 mV across a temperature difference of 53 K. Additionally, the prototype generates a maximum power output of 7.2 µW with a 40 K temperature difference and can produce 13 mV output voltage when subjected to around a 10 K temperature gradient when the cold side temperature is maintained at 308 K. Moreover, leveraging body heat with just a 1 K temperature variance between the body and the surrounding environment, the prototype could yield an impressive voltage output of 1.6 mV, marking the highest reported voltage output from human body heat to date. Our study not only introduces a cost-effective method for producing high-performance flexible thermoelectric films but also highlights their potential applications in wearable and implantable electronics.

Machine learning predicts peak oxygen uptake and peak power output for customizing cardiopulmonary exercise testing using non-exercise features.

PURPOSE: Cardiopulmonary exercise testing (CPET) is considered the gold standard for assessing cardiorespiratory fitness. To ensure consistent performance of each test, it is necessary to adapt the power increase of the test protocol to the physical characteristics of each individual. This study aimed to use machine learning models to determine individualized ramp protocols based on non-exercise features. We hypothesized that machine learning models will predict peak oxygen uptake ( V ˙ O2peak) and peak power output (PPO) more accurately than conventional multiple linear regression (MLR). METHODS: The cross-sectional study was conducted with 274 (♀168, ♂106) participants who performed CPET on a cycle ergometer. Machine learning models and multiple linear regression were used to predict V ˙ O2peak and PPO using non-exercise features. The accuracy of the models was compared using criteria such as root mean square error (RMSE). Shapley additive explanation (SHAP) was applied to determine the feature importance. RESULTS: The most accurate machine learning model was the random forest (RMSE: 6.52 ml/kg/min [95% CI 5.21-8.17]) for V ˙ O2peak prediction and the gradient boosting regression (RMSE: 43watts [95% CI 35-52]) for PPO prediction. Compared to the MLR, the machine learning models reduced the RMSE by up to 28% and 22% for prediction of V ˙ O2peak and PPO, respectively. Furthermore, SHAP ranked body composition data such as skeletal muscle mass and extracellular water as the most impactful features. CONCLUSION: Machine learning models predict V ˙ O2peak and PPO more accurately than MLR and can be used to individualize CPET protocols. Features that provide information about the participant's body composition contribute most to the improvement of these predictions. TRIAL REGISTRATION NUMBER: DRKS00031401 (6 March 2023, retrospectively registered).

Racing Demands for Winning a Grand Tour: Differences and Similarities Between a Female and a Male Winner.

PURPOSE: To describe and compare the race characteristics, demands, and durability profile of a male and a female Grand Tour winner. METHODS: Overall and stage-type-specific (ie, time trials, flat, semimountainous, and mountain) demands and race characteristics during 2 Grand Tours were determined and compared between the female and male cyclists. In addition, relative power output distribution and pacing, percentage of functional threshold power (FTP), and changes in maximal mean power outputs (MMPs) with increasing levels of kilojoules burned were determined. RESULTS: Although many differences were found between course and absolute racing demands between the male (FTP: 413 W; critical power: 417 W) and female (FTP: 297 W; critical power: 297 W) cyclists, similar power distributions and pacing strategies were found if data were expressed relatively. However, the female cyclist rode a higher percentage of her FTP during the first 2 quarters of flat stages (14.7%-15.1%) and the last quarter of mountain stages (9.8%) than the male cyclist. Decrements in MMPs were only observed after burning 30 kJ·kg-1 in the female and 45 kJ·kg-1 in the male Grand Tour winner. CONCLUSIONS: Both the male and female Grand Tour winners produced very high 20- to 60-minute MMPs, whereas decrements in MMPs were only observed after having burned 75% (female) and 80% (male) of total kilojoules burned during a stage. These are the latest and lowest in MMPs reported in the scientific literature and highlight the importance of durability in combination with excellent climbing and time-trial skills, which are needed to be able to win a Grand Tour.

Effects of different ischemic pressures on bar velocity during the bench press exercise: A randomized crossover trial.

The main objective of this study was to evaluate the effects of different ischemic pressures applied during rest intervals on bar velocity during the bench press exercise. 10 resistance-trained males (age = 23.2 ± 2.7 years; body mass = 83.9 ± 9 kg; body height = 181 ± 5.2 cm; bench press 1 repetition maximum (1RM) = 125 ± 16.4 kg; training experience = 5.4 ± 3.4 years) participated in the study. During 4 experimental sessions, following a randomized crossover design, the subjects performed 5 sets of 3 repetitions of the bench press exercise with a load of 60% 1RM under conditions: with ischemia (50% or 80% of arterial occlusion pressure), with SHAM ischemia (20 mmHg) and without ischemia (control condition). For the ischemic conditions cuffs were applied before each set for 6.5 min and released 30 s before the start of the set as reperfusion (6.5 min ischemia + 0.5 min reperfusion). In the control condition, ischemia was not applied. The two-way repeated measures ANOVA showed no significant condition × set interaction for mean bar velocity (MV; p = 0.17) and peak bar velocity (PV; p = 0.66). There was also no main effect of condition for MV (p = 0.58) and PV (p = 0.61). The results indicate that ischemic or SHAM treatment (6.5 minutes ischemia or SHAM + 30 s reperfusion) does not affect mean and peak bar velocity during the bench press exercise regardless of the applied pressure.

Cardiac power output is associated with adverse outcomes in patients with preserved ejection fraction after transcatheter aortic valve implantation.

Aims: Cardiac power output (CPO) measures cardiac performance, and its prognostic significance in heart failure with preserved ejection fraction (EF) has been previously reported. However, the effectiveness of CPO in risk stratification of patients with valvular heart disease and post-operative valvular disease has not been reported. We aimed to determine the association between CPO and clinical outcomes in patients with preserved left ventricular (LV) EF after transcatheter aortic valve implantation (TAVI). Methods and results: This retrospective observational study included 1047 consecutive patients with severe aortic stenosis after TAVI. All patients were followed up for all-cause mortality and hospitalization for HF. CPO was calculated as 0.222 × cardiac output × mean blood pressure (BP)/LV mass, where 0.222 was the conversion constant to W/100 g of the LV myocardium. CPO was assessed using transthoracic echocardiography at discharge after TAVI. Of the 1047 patients, 253 were excluded following the exclusion criteria, including those with low LVEF, and 794 patients (84.0 [80.0-88.0] years; 35.8% male) were included in this study. During a median follow-up period of 684 (237-1114) days, the composite endpoint occurred in 196 patients. A dose-dependent association was observed between the CPO levels and all-cause mortality. Patients in the lowest CPO tertile had significantly lower event-free survival rates (log-rank test, P = 0.043). Multivariate Cox regression analysis showed that CPO was independently associated with adverse outcomes (hazard ratio = 0.561, P = 0.020). CPO provided an incremental prognostic effect in the model based on clinical and echocardiographic markers (P = 0.034). Conclusion: CPO is independently and incrementally associated with adverse outcomes in patients with preserved LVEF following TAVI.

Effect of caffeine ingestion on time trial performance in cyclists: a systematic review and meta-analysis.

BACKGROUND: Caffeine, widely recognized as an ergogenic aid, has undergone extensive research, demonstrating its effectiveness to enhance endurance performance. However, there remains a significant gap in systematically evaluating its effects on time trial (TT) performance in cyclists. PURPOSE: This meta-analysis aimed to determine the efficacy of caffeine ingestion to increase cycling TT performance in cyclists and to evaluate the optimal dosage range for maximum effect. METHODS: A search of four databases was completed on 1 December 2023. The selected studies comprised crossover, placebo-controlled investigations into the effects of caffeine ingestion on cycling TT performance. Completion time (Time) and mean power output (MPO) were used as performance measures for TT. Meta-analyses were performed using a random-effects model to assess the standardized mean differences (SMD) in individual studies. RESULTS: Fifteen studies met the inclusion criteria for the meta-analyses. Subgroup analysis showed that moderate doses of caffeine intake (4-6 mg/kg) significantly improved cycling performance (SMD Time = -0.55, 95% confidence interval (CI) = -0.84 ~ -0.26, p < 0.01, I2 = 35%; SMD MPO = 0.44, 95% CI = 0.09 ~ 0.79, p < 0.05, I2 = 39%), while the effects of low doses (1-3 mg/kg) of caffeine were not significant (SMD Time = -0.34, 95% CI = -0.84 ~ 0.17, p = 0.19, I2 = 0%; SMD MPO = 0.31, 95% CI = -0.02 ~ 0.65, p = 0.07, I2 = 0%). CONCLUSION: A moderate dosage (4-6 mg/kg) of caffeine, identified as the optimal dose range, can significantly improve the time trial performance of cyclists, while a low dose (1-3 mg/kg) does not yield improvement. In addition, the improvements in completion time and mean power output resulting from a moderate dose of caffeine are essentially the same in cycling time trails.

Influence of Conventional Resistance Training Compared to Core Exercises on Road Cycling Power Output.

Conventional strength training and core exercises are commonly prescribed to improve cycling performance. Although previous studies have explored the utility of strength training in various cycling populations, this intervention has never been compared to core exercises. Thirty-six trained road cyclists were divided into three groups of 12 participants that performed either no strength training, conventional strength training, or core exercises, in all cases together with their regular cycling training during a 12-week period. Peak power outputs (POs) across different durations (five seconds, 60 seconds, five minutes, and 20 minutes) were recorded before and after the intervention. The results of the present study showed higher increases in relative PO with conventional strength training when compared to core training and no strength training for all measured durations: five-second Δ = 1.25 W/kg vs 0.47 W/kg and -0.17 W/kg; 60-second (Δ = 0.51 W/kg vs 0.13 W/kg and 0.02 W/kg; five-minute Δ = 0.22 W/kg vs 0.06 W/kg and 0.05 W/kg; and 20-minute Δ = 0.22 W/kg vs 0.07 W/kg and 0.06 W/kg. According to the data obtained in this study, conventional strength training is superior to core exercises, and no strength training was performed by trained road cyclists. Accordingly, it is recommended that this population incorporates strength training during their regular weekly workouts.

Pulmonary artery elastance as a predictor of hospital mortality in heart failure cardiogenic shock.

AIMS: The initial bundle of cares strongly affects haemodynamics and outcomes in acute decompensated heart failure cardiogenic shock (ADHF-CS). We sought to characterize whether 24 h haemodynamic profiling provides superior prognostic information as compared with admission assessment and which haemodynamic parameters best predict in-hospital death. METHODS AND RESULTS: All patients with ADHF-CS and with available admission and 24 h invasive haemodynamic assessment from two academic institutions were considered for this study. The primary endpoint was in-hospital death. Regression analyses were run to identify relevant predictors of study outcome. We included 127 ADHF-CS patients [65 (inter-quartile range 52-72) years, 25.2% female]. Overall, in-hospital mortality occurred in 26.8%. Non-survivors were older, with greater CS severity. Among admission variables, age [odds ratio (OR) = 1.06; 95% confidence interval (CI): 1.02-1.11; Padj = 0.005] and CPIRAP (OR = 0.62 for 0.1 increment; 95% CI: 0.39-0.95; Padj = 0.034) were found significantly associated with in-hospital death. Among 24 h haemodynamic univariate predictors of in-hospital death, pulmonary elastance (PaE) was the strongest (area under the curve of 0.77; 95% CI: 0.68-0.86). PaE (OR = 5.98; 95% CI: 2.29-17.48; Padj < 0.001), pulmonary artery pulsatility index (PAPi, OR = 0.77; 95% CI: 0.62-0.92; Padj = 0.013) and age (OR = 1.06; 95% CI: 1.02-1.11; Padj = 0.010) were independently associated with in-hospital death. Best cut-off for PaE was 0.85 mmHg/mL and for PAPi was 2.95; cohort phenotyping based on these PaE and PAPi thresholds further increased in-hospital death risk stratification; patients with 24 h high PaE and low PAPi exhibited the highest in-hospital mortality (56.2%). CONCLUSIONS: Pulmonary artery elastance has been found to be the most powerful 24 h haemodynamic predictor of in-hospital death in patients with ADHF-CS. Age, 24 h PaE, and PAPi are independently associated with hospital mortality. PaE captures ventricular (RV) afterload mismatch and PAPi provides a metric of RV adaptation, thus their combination generates four distinct haemodynamic phenotypes, enhancing in-hospital death risk stratification.

Vacancy Suppression and Resonant Level Rendering Extraordinary Power Factor in Sn0.99In0.01Te/Tourmaline Composite.

SnTe, as a potential medium-temperature thermoelectric material, reaches a maximum power factor (PF) usually above 750 K, which is not conducive to continuous high-power output in practical applications. In this study, PF is maintained at high values between 18.5 and 25 µW cm-1 K-2 for Sn0.99In0.01Te-x wt% tourmaline samples within the temperature range of 323 to 873 K, driving the highest PFeng of 1.2 W m-1 K-1 and PFave of 22.5 µW cm-1 K-2, over 2.5 times that of pristine SnTe. Such an extraordinary PF is attributed to the synergy of resonant levels and Sn vacancy suppression. Specifically, the Seebeck coefficient increases dramatically, reaching 88 µV K-1 at room temperature. Meanwhile, by Sn vacancy suppression, carrier concentration, and mobility are optimized to ≈1019 cm-3 and 740 cm2 V-1 s-1, respectively. With the tourmaline compositing, Sn vacancies are further suppressed and the thermal conductivity simultaneously decreases, with the minimum lattice thermal conductivity of 0.9 W m-1 K-1. Finally, the zT value ≈0.8 is obtained in the Sn0.99In0.01Te sample. The peak of the power output density reaches 0.89 W cm-2 at a temperature difference of 600 K. Such SnTe alloys with high and "temperature-independent" PF will offer an option for realizing high output power in thermoelectric devices.

Age-related blunting of serial sarcomerogenesis and mechanical adaptations following 4 wk of maximal eccentric resistance training.

During aging, muscles undergo atrophy, which is partly accounted for by a loss of sarcomeres in series. Serial sarcomere number (SSN) is associated with aspects of muscle mechanical function including the force-length and force-velocity-power relationships; hence, the age-related loss of SSN contributes to declining performance. Training emphasizing eccentric contractions increases SSN in young healthy rodents; however, the ability for eccentric training to increase SSN in old age is unknown. Ten young (8 mo) and 11 old (32 mo) male Fisher344/BN rats completed 4 wk of unilateral eccentric plantar flexion training. Pre- and posttraining, the plantar flexors were assessed for the torque-frequency, passive torque-angle, and torque-velocity-power relationships. The soleus, lateral gastrocnemius (LG), and medial gastrocnemius (MG) were harvested for SSN assessment via laser diffraction, with the untrained leg used as a control. In the untrained leg/pretraining, old rats had lower SSN in the soleus, LG, and MG, lower maximum torque, power, and shortening velocity, and greater passive torque than young. Young showed increased soleus and MG SSN following training. In contrast, old had no change in soleus SSN and experienced SSN loss in the LG. Pre- to posttraining, young experienced an increase in maximum isometric torque, whereas old had reductions in maximum torque, shortening velocity, and power, and increased passive torque. Our results show that although young muscle has the ability to add sarcomeres in response to maximal eccentric training, this stimulus could be not only ineffective, but also detrimental to aged muscle leading to dysfunctional remodeling.NEW & NOTEWORTHY The loss of sarcomeres in series with age contributes to declining muscle performance. The present study investigated whether eccentric training could improve performance via serial sarcomere addition in old muscle, like in young muscle. Four weeks of maximal eccentric training induced serial sarcomere addition in the young rat plantar flexors and improved in vivo performance, however, led to dysfunctional remodeling accompanied by further impaired performance in old rats.

Renewable energy sources integration via machine learning modelling: A systematic literature review.

The use of renewable energy sources (RESs) at the distribution level has become increasingly appealing in terms of costs and technology, expecting a massive diffusion in the near future and placing several challenges to the power grid. Since RESs depend on stochastic energy sources -solar radiation, temperature and wind speed, among others- they introduce a high level of uncertainty to the grid, leading to power imbalance and deteriorating the network stability. In this scenario, managing and forecasting RES uncertainty is vital to successfully integrate them into the power grids. Traditionally, physical- and statistical-based models have been used to predict RES power outputs. Nevertheless, the former are computationally expensive since they rely on solving complex mathematical models of the atmospheric dynamics, whereas the latter usually consider linear models, preventing them from addressing challenging forecasting scenarios. In recent years, the advances in machine learning techniques, which can learn from historical data, allowing the analysis of large-scale datasets either under non-uniform characteristics or noisy data, have provided researchers with powerful data-driven tools that can outperform traditional methods. In this paper, a systematic literature review is conducted to identify the most widely used machine learning-based approaches to forecast RES power outputs. The results show that deep artificial neural networks, especially long-short term memory networks, which can accurately model the autoregressive nature of RES power output, and ensemble strategies, which allow successfully handling large amounts of highly fluctuating data, are the best suited ones. In addition, the most promising results of integrating the forecasted output into decision-making problems, such as unit commitment, to address economic, operational and managerial grid challenges are discussed, and solid directions for future research are provided.

Reliability and validity of a non-linear index of heart rate variability to determine intensity thresholds.

Exercise intensity distribution is crucial for exercise individualization, prescription, and monitoring. As traditional methods to determine intensity thresholds present limitations, heart rate variability (HRV) using DFA a1 has been proposed as a biomarker for exercise intensity distribution. This index has been associated with ventilatory and lactate thresholds in previous literature. This study aims to assess DFA a1's reliability and validity in determining intensity thresholds during an incremental cycling test in untrained healthy adults. Sixteen volunteers (13 males and 3 females) performed two identical incremental cycling stage tests at least 1 week apart. First and second ventilatory thresholds, lactate thresholds, and HRV thresholds (DFA a1 values of 0.75 and 0.5 for HRVT1 and HRVT2, respectively) were determined in heart rate (HR), relative oxygen uptake (VO2rel), and power output (PO) values for both tests. We used intraclass correlation coefficient (ICC), change in mean, and typical error for the reliability analysis, and paired t-tests, correlation coefficients, ICC, and Bland-Altman analysis to assess the agreement between methods. Regarding reliability, HRV thresholds showed the best ICCs when measured in PO (HRVT1: ICC = .87; HRVT2: ICC = .97), comparable to ventilatory and lactate methods. HRVT1 showed the strongest agreement with LA 2.5 in PO (p = 0.09, r = .93, ICC = .93, bias = 9.9 ± 21.1), while HRVT2 reported it with VT2 in PO (p = 0.367, r = .92, ICC = .92, bias = 5.3 ± 21.9). DFA a1 method using 0.75 and 0.5 values is reliable and valid to determine HRV thresholds in this population, especially in PO values.