scholarly journals The Global Session Metric Score (GSMs): A Modified Session-Specific Exertional Index

2021 ◽  
Vol 3 ◽  
Author(s):  
Hanna M. Gardner ◽  
Andrew W. Scheck ◽  
John R. Cone ◽  
Nathaniel T. Berry ◽  
Laurie Wideman
Keyword(s):  
Heart Rate ◽  
High Intensity ◽  
Cost Effective ◽  
Weather Conditions ◽  
Training Load ◽  
Subsequent Performance ◽  
Cost Effective Alternative ◽  
Training Stress ◽  
The Individual ◽  
Muscle Actions

Monitoring session training load to optimize the training stress that drives athlete adaptation and subsequent performance, is fundamental to periodization and programming. Analyzing the internal load experienced by the individual in response to the external load prescribed by coaching staff is crucial to avoid overtraining and optimize training adaptation. Subjective measures provide more information regarding individual training load, as heart rate measures alone do not account for collisions, eccentric muscle actions, muscle soreness, weather conditions, or accumulated training loads, which are paramount to the athlete experience. However, the current subjective metric for interpreting session training load (sRPE) is poorly shaped to the athlete's global response to the whole session, often showing poorer correlations to heart rate (HR) measures during intermittent or high-intensity activity. This study introduces a new metric, the Global Session Metric Score (GSMs), which creates a symmetrical relation between the verbal descriptor and numeric values, as well as more applicable session-specific verbal descriptors for the highest level of exertion. Twenty-four D1 male college soccer field players (age: 20.5 +/– 1.42) wore HR monitors and reported GSMs for all practices and games within an entire season. Linear regression with 10-fold cross validation was used to test the relation between GSMs with B-TRIMP and E-TRIMP, respectively. These models demonstrate good performance with consistency and reliability in the estimation of GSMs to predict both B-TRIMP (R2 = 0.75–0.77) and E-TRIMP (R2 = 0.76–0.78). The findings show promise for the GSMs index as a reliable means for measuring load in both training and matches during a high-intensity intermittent team sport. Future studies should directly compare GSMs to the existing sRPE scale within a controlled laboratory setting and across various other sports. GSMs provides coaches and clinicians a simple and cost-effective alternative to heart rate monitors, as well as a proficient measure of internal training load experienced by the individual.

scholarly journals Associations Between Selected Training-Stress Measures and Fitness Changes in Male Soccer Players

2019 ◽  
Vol 14 (8) ◽  
pp. 1050-1057 ◽  
Author(s):  
Alireza Rabbani ◽  
Mehdi Kargarfard ◽  
Carlo Castagna ◽  
Filipe Manuel Clemente ◽  
Craig Twist
Keyword(s):  
Heart Rate ◽  
High Intensity ◽  
Soccer Players ◽  
Running Performance ◽  
Total Distance ◽  
Professional Soccer ◽  
Before And After ◽  
Body Load ◽  
Training Stress ◽  
Training Impulse

Purpose: To investigate the relationship between accumulated global positioning system–accelerometer-based and heart rate–based training metrics and changes in high-intensity intermittent-running capacity during an in-season phase in professional soccer players. Methods: Eleven male professional players (mean [SD] age 27.2 [4.5] y) performed the 30-15 Intermittent Fitness Test (30-15IFT) before and after a 5-wk in-season training phase, and the final velocity (VIFT) was considered their high-intensity intermittent-running capacity. During all sessions, Edwards training impulse (Edwards TRIMP), Banister TRIMP, Z5 TRIMP, training duration, total distance covered, new body load (NBL), high-intensity running performance (distance covered above 14.4 km·h−1), and very-high-intensity running performance (distance covered above 19.8 km·h−1) were recorded. Results: The players’ VIFT showed a most likely moderate improvement (+4.3%, 90% confidence limits 3.1–5.5%, effect size 0.70, [0.51–0.89]). Accumulated NBL, Banister TRIMP, and Edwards TRIMP showed large associations (r = .51–.54) with changes in VIFT. A very large relationship was also observed between accumulated Z5 TRIMP (r = .72) with changes in VIFT. Large to nearly perfect within-individual relationships were observed between NBL and some of the other training metrics (ie, Edwards TRIMP, Banister TRIMP, training duration, and total distance) in 10 out of 11 players. Conclusions: Heart rate–based training metrics can be used to monitor high-intensity intermittent-running-capacity changes in professional soccer players. The dose–response relationship is also largely detected using accelerometer-based metrics (ie, NBL) to track changes in high-intensity intermittent-running capacity of professional soccer players.

Training Characteristics of Male and Female Professional Road Cyclists: A 4-Year Retrospective Analysis

2020 ◽  
Vol 15 (4) ◽  
pp. 534-540 ◽  
Author(s):  
Teun van Erp ◽  
Dajo Sanders ◽  
Jos J. de Koning
Keyword(s):  
Heart Rate ◽  
Retrospective Analysis ◽  
Perceived Exertion ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Training Intensity ◽  
Male And Female ◽  
Stress Score ◽  
Training Stress ◽  
Training Impulse

Purpose: To describe the training intensity and load characteristics of professional cyclists using a 4-year retrospective analysis. Particularly, this study aimed to describe the differences in training characteristics between men and women professional cyclists. Method: For 4 consecutive years, training data were collected from 20 male and 10 female professional cyclists. From those training sessions, heart rate, rating of perceived exertion, and power output (PO) were analyzed. Training intensity distribution as time spent in different heart rate and PO zones was quantified. Training load was calculated using different metrics such as Training Stress Score, training impulse, and session rating of perceived exertion. Standardized effect size is reported as Cohen’s d. Results: Small to large higher values were observed for distance, duration, kilojoules spent, and (relative) mean PO in men’s training (d = 0.44–1.98). Furthermore, men spent more time in low-intensity zones (ie, zones 1 and 2) compared with women. Trivial differences in training load (ie, Training Stress Score and training impulse) were observed between men’s and women’s training (d = 0.07–0.12). However, load values expressed per kilometer were moderately (d = 0.67–0.76) higher in women compared with men’s training. Conclusions: Substantial differences in training characteristics exist between male and female professional cyclists. Particularly, it seems that female professional cyclists compensate their lower training volume, with a higher training intensity, in comparison with male professional cyclists.

scholarly journals The Association Between Internal and External Measures of Training Load in Batsmen and Medium-Fast Bowlers During Net-Based Cricket Training

2017 ◽  
Vol 12 (2) ◽  
pp. 247-253 ◽  
Author(s):  
Will Vickery ◽  
Ben Dascombe ◽  
Rob Duffield
Keyword(s):  
Heart Rate ◽  
Multiple Regression ◽  
High Intensity ◽  
Perceived Exertion ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Stepwise Multiple Regression ◽  
Total Distance ◽  
Regression Techniques ◽  
External Training

Purpose:To examine the relationship between session rating of perceived exertion (sRPE) and measures of internal and external training load (TL) in cricket batsmen and medium-fast bowlers during net-based training sessions.Methods:The internal (heart rate), external (movement demands, PlayerLoad), and technical (cricket-specific skills) loads of 30 male cricket players (age 21.2 ± 3.8 y, height 1.82 ± 0.07 m, body mass 79.0 ± 8.7 kg) were determined from net-based cricket-training sessions (n = 118). The relationships between sRPE and measures of TL were quantified using Pearson product–moment correlations respective to playing position. Stepwise multiple-regression techniques provided key internal- and external-load determinants of sRPE in cricket players.Results:Significant correlations were evident (r = -.34 to .87, P < .05) between internal and external measures of TL and sRPE, with the strongest correlations (r ≥ .62) for GPS-derived measures for both playing positions. In batsmen, stepwise multiple-regression analysis revealed that 67.8% of the adjusted variance in sRPE could be explained by PlayerLoad and high-intensity distance (y = 27.43 + 0.81 PlayerLoad + 0.29 high-intensity distance). For medium-fast bowlers, 76.3% of the adjusted variance could be explained by total distance and mean heart rate (y = 101.82 + total distance 0.05 + HRmean – 0.48).Conclusion:These results suggest that sRPE is a valid method of reporting TL among cricket batsmen and medium-fast bowlers. Position-specific responses are evident and should be considered when monitoring the TL of cricket players.

Quantifying Training Load: A Comparison of Subjective and Objective Methods

2008 ◽  
Vol 3 (1) ◽  
pp. 16-30 ◽  
Author(s):  
Jill Borresen ◽  
Michael I. Lambert
Keyword(s):  
Heart Rate ◽  
High Intensity ◽  
Perceived Exertion ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Regression Equations ◽  
Training Time ◽  
Ad Libitum ◽  
Training Impulse ◽  
The Relationship

Purpose:To establish the relationship between a subjective (session rating of perceived exertion [RPE]) and 2 objective (training impulse [TRIMP]) and summated-heart-rate-zone (SHRZ) methods of quantifying training load and explain characteristics of the variance not accounted for in these relationships.Methods:Thirty-three participants trained ad libitum for 2 wk, and their heart rate (HR) and RPE were recorded to calculate training load. Subjects were divided into groups based on whether the regression equations over- (OVER), under- (UNDER), or accurately predicted (ACCURATE) the relationship between objective and subjective methods.Results:A correlation of r = .76 (95% CI: .56 to .88) occurred between TRIMP and session-RPE training load. OVER spent a greater percentage of training time in zone 4 of SHRZ (ie, 80% to 90% HRmax) than UNDER (46% ± 8% vs 25% ± 10% [mean ± SD], P = .008). UNDER spent a greater percentage of training time in zone 1 of SHRZ (ie, 50% to 60% HRmax) than OVER (15% ± 8% vs 3% ± 3%, P = .005) and ACCURATE (5% ± 3%, P = .020) and more time in zone 2 of SHRZ (ie, 60% to 70%HRmax) than OVER (17% ± 6% vs 7% ± 6%, P = .039). A correlation of r = .84 (.70 to .92) occurred between SHRZ and session-RPE training load. OVER spent proportionally more time in Zone 4 than UNDER (45% ± 8% vs 25% ± 10%, P = .018). UNDER had a lower training HR than ACCURATE (132 ± 10 vs 148 ± 12 beats/min, P = .048) and spent more time in zone 1 than OVER (15% ± 8% vs 4% ± 3%, P = .013) and ACCURATE (5% ± 3%, P = .015).Conclusions:The session-RPE method provides reasonably accurate assessments of training load compared with HR-based methods, but they deviate in accuracy when proportionally more time is spent training at low or high intensity.

scholarly journals Synthetic 3D Recording of a Shipwreck Embedded in Seafloor Sediments: Distinguishing Internal Details

Heritage ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 541-553
Author(s):  
Lars O. Boldreel ◽  
Ole Grøn ◽  
Deborah Cvikel
Keyword(s):  
High Resolution ◽  
Cost Effective ◽  
Weather Conditions ◽  
Effective Alternative ◽  
3D Image ◽  
Experimental Basis ◽  
Dense Grid ◽  
Cost Effective Alternative ◽  
Seafloor Sediments ◽  
Harbour Area

3D recording of shipwrecks completely buried in seafloor sediments has great potential as an important aspect of maritime archaeological surveys and management. Buried shipwrecks have been recorded directly with seismic 3D Chirp sub-bottom profilers on an experimental basis. This method is, however, expensive, time-consuming and complicated. This article outlines the application of a faster, cheaper, and less complicated method of synthetic 3D recording, which is also less sensitive to weather conditions. It involves the acquisition of a larger number of seismic 2D high-resolution sub-bottom profiles in a dense grid that does not need to be regular. The method is based on the results of survey work conducted in the Akko Harbour area, on the Carmel coast of Israel, which shows that the shape of the hull of a shipwreck can be precisely determined, and that the sedimentary units bounding it can be outlined and interpreted. Based on an interpretation of the shape of the hull, the depth of the structure was measured, and a 3D image of the shipwreck was subsequently generated. Samples of the sub-seafloor were obtained across the area, and the sample located within the area of the mapped shipwreck was found to contain wood fragments and a piece of rope. This article demonstrates that 2D surveying is a viable and cost-effective alternative to 3D surveying that is able to produce good results.

scholarly journals The Influence of Training Load on Hematological Athlete Biological Passport Variables in Elite Cyclists

2021 ◽  
Vol 3 ◽  
Author(s):  
Tiffany Astolfi ◽  
Fabienne Crettaz von Roten ◽  
Bengt Kayser ◽  
Martial Saugy ◽  
Raphael Faiss
Keyword(s):  
Hemoglobin Concentration ◽  
Training Load ◽  
Maximal Power Output ◽  
Biological Passport ◽  
Hemoglobin Mass ◽  
Training Stress ◽  
The Individual ◽  
Elite Cyclists ◽  
Over Time ◽  
Chronic Training

The hematological module of the Athlete Biological Passport (ABP) is used in elite sport for antidoping purposes. Its aim is to better target athletes for testing and to indirectly detect blood doping. The ABP allows to monitor hematological variations in athletes using selected primary blood biomarkers [hemoglobin concentration (Hb) and reticulocyte percentage (Ret%)] with an adaptive Bayesian model to set individual upper and lower limits. If values fall outside the individual limits, an athlete may be further targeted and ultimately sanctioned. Since (Hb) varies with plasma volume (PV) fluctuations, possibly caused by training load changes, we investigated the putative influence of acute and chronic training load changes on the ABP variables. Monthly blood samples were collected over one year in 10 male elite cyclists (25.6 ± 3.4 years, 181 ± 4 cm, 71.3 ± 4.9 kg, 6.7 ± 0.8 W.kg−1 5-min maximal power output) to calculate individual ABP profiles and monitor hematological variables. Total hemoglobin mass (Hbmass) and PV were additionally measured by carbon monoxide rebreathing. Acute and chronic training loads–respectively 5 and 42 days before sampling–were calculated considering duration and intensity (training stress score, TSSTM). (Hb) averaged 14.2 ± 0.0 (mean ± SD) g.dL−1 (range: 13.3–15.5 g·dl−1) over the study with significant changes over time (P = 0.004). Hbmass was 1030 ± 87 g (range: 842–1116 g) with no significant variations over time (P = 0.118), whereas PV was 4309 ± 350 mL (range: 3,688–4,751 mL) with a time-effect observed over the study time (P = 0.014). Higher acute–but not chronic—training loads were associated with significantly decreased (Hb) (P &lt;0.001). Although individual hematological variations were observed, all ABP variables remained within the individually calculated limits. Our results support that acute training load variations significantly affect (Hb), likely due to short-term PV fluctuations, underlining the importance of considering training load when interpreting individual ABP variations for anti-doping purposes.

scholarly journals Heart Rate Responses and Training Load During Nonspecific and Specific Aerobic Training in Adolescent Taekwondo Athletes

2011 ◽  
Vol 29 (1) ◽  
pp. 59-66 ◽  
Author(s):  
Monoem Haddad ◽  
Anis Chaouachi ◽  
Del Wong ◽  
Carlo Castagna ◽  
Karim Chamari
Keyword(s):  
Heart Rate ◽  
Short Duration ◽  
High Intensity ◽  
Perceived Exertion ◽  
Aerobic Training ◽  
Interval Training ◽  
Technical Skills ◽  
Training Load ◽  
Training Methods ◽  
And Training

Heart Rate Responses and Training Load During Nonspecific and Specific Aerobic Training in Adolescent Taekwondo AthletesThe efficacy of replacing generic running with Taekwondo (TKD) specific technical skills during interval training at an intensity corresponding to 90-95% of maximum heart rate (HRmax) has not yet been demonstrated. Therefore, the purpose of this study was to compare the HR responses and perceived exertion between controlled running and high-intensity TKD technical interval training in adolescent TKD athletes. Eighteen adolescent, male TKD athletes performed short-duration interval running and TKD specific technical skills (i.e. 10-20 [10-s of exercise interspersed with 20 s of passive recovery]) in a counterbalanced design. In both training methods, HR was measured and expressed as the percentage of HR reserve (%HRres). Rating of perceived exertion (RPE, Borg's category rating-10 scale), Banister's training impulse (TRIMP) and Edwards' training load (TL) were used to quantify the internal training load. Recorded cardiovascular responses expressed in %HRresin the two training methods were not significantly different (p > 0.05). Furthermore, the two training methods induced similar training loads as calculated by Banister and Edwards' methods. Perceived exertion ranged between "hard" and "very hard" during all interval training sessions. These findings showed that performing repeated TKD specific skills increased HR to the same level, and were perceived as producing the same training intensity as did short-duration interval running in adolescent TKD athletes. Therefore, using specific TKD kicking exercises in high-intensity interval training can be applied to bring more variety during training, mixing physical and technical aspects of the sport, while reaching the same intensity as interval running.

scholarly journals PL-004 Research on monitoring power endurance training effect of synchronized swimmers

2018 ◽  
Vol 1 (1) ◽  
Author(s):  
Yuncai Fan ◽  
Qi Yan
Keyword(s):  
Heart Rate ◽  
Physical Training ◽  
High Intensity ◽  
Load Level ◽  
Training Load ◽  
Maximum Heart Rate ◽  
Quick Recovery ◽  
Before And After ◽  
High Intensity Interval ◽  
And Training

Objective To explore the usage of heart rate and derivative index, such as quick recovery index (QRI) and training impulse (TRIMP), to monitor and evaluate load level at physical training course. With simplified load evaluation program, we can accurately feedback load stress and recovery conditions of the athletes, so as to timely adjust training load and avoid sports fatigue. Methods Maximum oxygen uptake is tested to determine maximum heart rate of the athletes, which can be used as the basis for monitoring assessment of physical training load. During training phase, monitoring the variation of the relative index of HR and sleeping conditions of 10 athletes by Firstbeat. The test means was High-intensity interval endurance of climbing machine in 7*20s-20s before and after stage training. The main indexes include of QRI/TRIMP/EPOC/BLa\climbing height.  Results It’s shown through monitoring that maximum heart rate of the athletes in the physical training course is up to 200BPM, which prompts high load level during training. Such athletic ability is promoted to satisfy the demands for complex choreography. Characteristics of energy supply for power endurance with high intensity closely agree with physical fitness demand during synchronized swimming competition, which is general performance of strength, speed and endurance. Through comparison of data on testing power endurance of climbing machine in 7*20s-20S before and after training, average climbing height of the athletes is increased from 60.1m/20s to 62.4m/20s with increased range up to 3.8% and blood lactate level is decreased from 10.7mmol/L to 10.5mmol/L in 2 minutes after exercise, which can be regarded as slightly improvement of ability of the athletes for lactate decomposition and fatigue relief, and aerobic capacity of the athletes are improved to a certain degree. After training, heart rate QRI and TRIMP of the athletes are improved slightly. Among them, QRI is significantly improved from 19.6% to 21.6% after stage training, which shows slightly improvement of training quality and recovery capability of the athletes, i.e. adaptive capacity to training load; After physical training, research on monitoring QRI of the athletes during arrangement and relaxation shows that maximum heart rate level without voice guidance is 75.1bpm,which is higher than those with voice guidance 72.9bmp after 5-min quick recovery; QRI of the athletes is 31.9% when voice is used to guide relaxation, which is significantly higher than those without relaxation under voice guidance (QRI is 27.0%); night pressure monitoring unit (BodyGuard2) of Firstbeat is used to monitor sleeping conditions of the athletes. In the initial stage of heavy load training cycle, training load enables athletes to produce a strong stress response, which causes relatively poor sleeping and recovery conditions; with gradual adaptation of the athletes to the training load, in the middle and later stages of the cycle, stress response of the athletes during sleeping almost disappears, and their sleeping quality and recovery conditions are improved significantly.  Conclusions Through Power endurance training, lactate elimination capacity of the athletes, i.e. anti-fatigue capacity and quick recovery capability are improved; during quick recovery of the athletes, voice guidance can be used to effectively promote quick recovery of the athletes. Exercise heart rate, TRIMP and QRI can be used to perceptually and rapidly monitor completion of physical training load in a real-time way, Objective to evaluate recovery and sleeping conditions of the athletes, and effectively evaluate high-intensity interval physical training load and training effect.

scholarly journals Continuous Versus Intermittent Running: Acute Performance Decrement and Training Load

2021 ◽  
pp. 1-10
Author(s):  
Antonis Kesisoglou ◽  
Andrea Nicolò ◽  
Lucinda Howland ◽  
Louis Passfield
Keyword(s):  
Perceived Exertion ◽  
Time Trial ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Performance Decrement ◽  
Running Training ◽  
Subsequent Performance ◽  
Training Stress ◽  
And Training ◽  
Opposite Response

Purpose: To examine the effect of continuous (CON) and intermittent (INT) running training sessions of different durations and intensities on subsequent performance and calculated training load (TL). Methods: Runners (N = 11) performed a 1500-m time trial as a baseline and after completing 4 different running training sessions. The training sessions were performed in a randomized order and were either maximal for 10 minutes (10CON and 10INT) or submaximal for 25 minutes (25CON and 25INT). An acute performance decrement (APD) was calculated as the percentage change in 1500-m time-trial speed measured after training compared with baseline. The pattern of APD response was compared with that for several TL metrics (bTRIMP, eTRIMP, iTRIMP, running training stress score, and session rating of perceived exertion) for the respective training sessions. Results: Average speed (P < .001, ) was different for each of the initial training sessions, which all resulted in a significant APD. This APD was similar when compared across the sessions except for a greater APD found after 10INT versus 25CON (P = .02). In contrast, most TL metrics were different and showed the opposite response to APD, being higher for CON versus INT and lower for 10- versus 25-minute sessions (P < .001, ). Conclusion: An APD was observed consistently after running training sessions, but it was not consistent with most of the calculated TL metrics. The lack of agreement found between APD and TL suggests that current methods for quantifying TL are flawed when used to compare CON and INT running training sessions of different durations and intensities.

scholarly journals Influencia del Volumen e Intensidad de la Carga de Entrenamiento en la Frecuencia Cardiaca de Recuperación (Influence of Training Load Volume and Intensity on Heart Rate Recovery)

Retos ◽  
2016 ◽  
pp. 180-183
Author(s):  
Roberto Andrés González-Fimbres ◽  
Héctor Griego Amaya ◽  
Claudia Selene Cuevas-Castro ◽  
Germán Hernández Cruz
Keyword(s):  
Heart Rate ◽  
High Intensity ◽  
Performance Enhancement ◽  
Heart Rate Recovery ◽  
High Volume ◽  
Training Load ◽  
Low Intensity ◽  
Load Volume ◽  
Low Volume ◽  
Intensity Training

Cuantificar los componentes de volumen e intensidad de la carga de entrenamiento es importante para garantizar la mejora del rendimiento. El objetivo de este estudio fue el comparar los efectos del volumen y la intensidad de la carga de entrenamiento sobre la Frecuencia Cardiaca de Recuperación (FCR). Dos mujeres y cuatro hombres, (edad M: 21 ± 1.41, H: 25.75 ± 4.57 años) entrenados en deportes de resistencia llevaron a cabo dos tratamientos con la misma carga interna (TRIMP = 52 unidades arbitrarias) pero con variación en volumen e intensidad (T1 = intensidad alta y volumen bajo [86-91% FCres, 14.5 min, T2 = intensidad baja y volumen alto [72-78% FCres, 30.5 min]). Posterior al ejercicio se monitoreó la FCR en cinco momentos: al finalizar el esfuerzo (R1), 10 (R2), 20 (R3), 30 (R4) y 40 (R5) minutos después del esfuerzo. Se encontraron diferencias significativas (p ≤ .05) entre los valores de FCR en los cinco momentos. Los resultados sugieren que tratamientos de la misma carga interna existen diferencias entre la carga interna de los tratamientos, observando que la intensidad afecta de mayor manera a la FCR que el volumen. Abstract. Quantifing the effects of volume and intensity components of training load (TL) is essential in order to guarantee performance enhancement. The aim of this study was to compare the effects of training load volume and intensity on Heart Rate Recovery (HRR). Two women (age = 21 ± 1.41) and four men (age = 25.75 ± 4.57 years) trained in endurance sports performed two different treatments with equal TL (TRIMP = 52 arbitrary units) but different volume and intensity (Training 1 = high intensity, low volume [86-91% HRres, 14.5 min], Training 2 = low intensity, high volume [72-78% HRres, 30.5 min]). HRR was monitored after exercise in five moments: at the end of training (R1), and 10 (R2), 20 (R3), 30 (R4), and 40 (R5) minutes after effort. Significant differences were found in HRR values at each of the five intervals (p ≤ .05). Results suggest the existence of significant differences in TL between the two treatments. Outcomes also evidenced that intensity has a greater effect than volume on HRR.

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