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The study explores the validity of the nonlinear index alpha 1 of detrended fluctuation analysis (DFAa1) of heart rate (HR) variability for exercise prescription in prolonged constant load running bouts of different intensities. 21 trained endurance athletes (9 w and 12 m) performed a ramp test for ventilatory threshold (vVT1 and vVT2) and DFAa1‐based (vDFAa1‐1 at 0.75 and vDFAa1‐2 at 0.5) running speed detection as well as two 20‐min running bouts at vDFAa1‐1 and vDFAa1‐2 (20‐vDFAa1‐1 and 20‐vDFAa1‐2), in which HR, oxygen consumption (VO2), respiratory frequency (RF), DFAa1, and blood lactate concentration [La‐] were assessed. 20‐vDFAa1‐2 could not be finished by all participants (finisher group (FG), n = 15 versus exhaustion group (EG), n = 6). Despite similar mean external loads of vDFAa1‐1 (10.6 ± 1.9 km/h) and vDFAa1‐2 (13.1 ± 2.4 km/h) for all participants compared to vVT1 (10.8 ± 1.7 km/h) and vVT2 (13.2 ± 1.9 km/h), considerable differences were present for 20‐vDFAa1‐2 in EG (15.2 ± 2.4 km/h). 20‐vDFAa1‐1 and 20‐DFAa1‐2 yielded significant differences in FG for HR (76.2 ± 5.7 vs. 86.4 ± 5.9 %HRPEAK), VO2 (62.1 ± 5.0 vs. 77.5 ± 8.6 %VO2PEAK), RF (40.6 ± 11.3 vs. 46.1 ± 9.8 bpm), DFA‐a1 (0.86 ± 0.23 vs. 0.60 ± 0.15), and [La‐] (1.41 ± 0.45 vs. 3.34 ± 2.24 mmol/L). Regarding alterations during 20‐vDFAa1‐1, all parameters showed small changes for all participants, while during 20‐vDFAa1‐2 RF and DFAa1 showed substantial alterations in FG (RF: 15.6% and DFAa1: −12.8%) and more pronounced in EG (RF: 20.1% and DFAa1: −35.9%). DFAa1‐based exercise prescription from incremental testing could be useful for most participants in prolonged running bouts, at least in the moderate to heavy intensity domain. In addition, an individually different increased risk of overloading may occur in the heavy to severe exercise domains and should be further elucidated in the light of durability and decoupling assessment. Highlights: DFAa1‐based exercise prescription from incremental testing shows potential for prolonged constant load exercise, at least in the moderate to heavy intensity domains for most trained runners.Caution is advised for the heavy to severe exercise domains as individual overload may occur.The relationship of DFAa1 and vDFAa1 seems to be highly individual as well as perspectives for the durability and decoupling assessment and should be further elucidated during longer exercise bouts. [ABSTRACT FROM AUTHOR]

Current research results demonstrate the potential of spatter reduction in laser deep penetration welding by using adapted laser beam intensity distributions between a ring and a core intensity. The spatter-reducing effect, resulting from the additional ring intensity, is often attributed to an enlarged keyhole opening. However, it remains a matter of debate how exactly an additional ring intensity influences the process. This study, therefore, investigates the effect of an increasing ring intensity on process dynamics and the spatter formation regime. Laser beam welding experiments were carried out on 2.4068 nickel hidden T-joints at different welding speeds of up to 16 m/min, as well as different intensity distributions, while maintaining a constant weld depth. The tests were evaluated by using two high-speed cameras from different angles to analyze spatter and their formation mechanisms as well as the keyhole opening. Metallographic analyses and x-ray images were used to determine influences on the seam shape and porosity. It was shown that a change in intensity distribution has a significant influence on the melt flow, the resulting amount of spatter, and the porosity, which is comparable across the investigated welding speeds. While a core-based power distribution leads to spatter formation on the rear of the keyhole opening, it was shown that a ring-based power distribution leads to spatter formation on both sides of the keyhole. With an optimal power distribution, spatter formation could be largely prevented. Based on these findings, the single wave regime, a stabilized regime, and a lateral spatter regime were identified. [ABSTRACT FROM AUTHOR]

Background: Determining thresholds by measuring blood lactate levels (lactate thresholds) or gas exchange (ventilatory thresholds) that delineate the different exercise intensity domains is crucial for training prescription. This systematic review with meta-analyses aims to assess the overall validity of the first and second heart rate variability - derived threshold (HRVT1 and HRVT2, respectively) by computing global effect sizes for agreement and correlation between HRVTs and reference – lactate and ventilatory (LT-VTs) – thresholds. Furthermore, this review aims to assess the impact of subjects' characteristics, HRV methods, and study protocols on the agreement and correlation between LT-VTs and HRVTs. Methods: Systematic computerised searches for studies determining HRVTs during incremental exercise in humans were conducted. The agreements and correlations meta-analyses were conducted using a random-effect model. Causes of heterogeneity were explored by subgroup analysis and meta-regression with subjects' characteristics, incremental exercise protocols, and HRV methods variables. The methodological quality was assessed using QUADAS-2 and STARDHRV tools. The risk of bias was assessed by funnel plots, fail-safe N test, Egger's test of the intercept, and the Begg and Mazumdar rank correlation test. Results: Fifty included studies (1160 subjects) assessed 314 agreements (95 for HRVT1, 219 for HRVT2) and 246 correlations (82 for HRVT1, 164 for HRVT2) between LT-VTs and HRVTs. The standardized mean differences were trivial between HRVT1 and LT1-VT1 (SMD = 0.08, 95% CI -0.04–0.19, n = 22) and between HRVT2 and LT2-VT2 (SMD = -0.06, 95% CI -0.15–0.03, n = 42). The correlations were very strong between HRVT1 and LT1-VT1 (r = 0.85, 95% CI 0.75–0.91, n = 22), and between HRVT2 and LT2-VT2 (r = 0.85, 95% CI 0.80–0.89, n = 41). Moreover, subjects' characteristics, type of ergometer, or initial and incremental workload had no impact on HRVTs determination. Conclusion: HRVTs showed trivial differences and very strong correlations with LT-VTs and might thus serve as surrogates. These results emphasize the usefulness of HRVTs as promising, accessible, and cost-effective means for exercise and clinical prescription purposes. Key Points: HRV-derived thresholds (HRVT1 and HRVT2) showed trivial standardised mean differences and very strong correlations with their respective reference thresholds (lactate and ventilatory). Subjects' characteristics, ergometer, or initial and incremental workload did not impact HRVTs determination. HRVT2 is accurately determined by frequency-domain and non-linear HRV indices, and by using short increments during graded exercise tests. [ABSTRACT FROM AUTHOR]

Abstract Background Determining thresholds by measuring blood lactate levels (lactate thresholds) or gas exchange (ventilatory thresholds) that delineate the different exercise intensity domains is crucial for training prescription. This systematic review with meta-analyses aims to assess the overall validity of the first and second heart rate variability - derived threshold (HRVT1 and HRVT2, respectively) by computing global effect sizes for agreement and correlation between HRVTs and reference – lactate and ventilatory (LT-VTs) – thresholds. Furthermore, this review aims to assess the impact of subjects’ characteristics, HRV methods, and study protocols on the agreement and correlation between LT-VTs and HRVTs. Methods Systematic computerised searches for studies determining HRVTs during incremental exercise in humans were conducted. The agreements and correlations meta-analyses were conducted using a random-effect model. Causes of heterogeneity were explored by subgroup analysis and meta-regression with subjects’ characteristics, incremental exercise protocols, and HRV methods variables. The methodological quality was assessed using QUADAS-2 and STARDHRV tools. The risk of bias was assessed by funnel plots, fail-safe N test, Egger’s test of the intercept, and the Begg and Mazumdar rank correlation test. Results Fifty included studies (1160 subjects) assessed 314 agreements (95 for HRVT1, 219 for HRVT2) and 246 correlations (82 for HRVT1, 164 for HRVT2) between LT-VTs and HRVTs. The standardized mean differences were trivial between HRVT1 and LT1-VT1 (SMD = 0.08, 95% CI -0.04–0.19, n = 22) and between HRVT2 and LT2-VT2 (SMD = -0.06, 95% CI -0.15–0.03, n = 42). The correlations were very strong between HRVT1 and LT1-VT1 (r = 0.85, 95% CI 0.75–0.91, n = 22), and between HRVT2 and LT2-VT2 (r = 0.85, 95% CI 0.80–0.89, n = 41). Moreover, subjects’ characteristics, type of ergometer, or initial and incremental workload had no impact on HRVTs determination. Conclusion HRVTs showed trivial differences and very strong correlations with LT-VTs and might thus serve as surrogates. These results emphasize the usefulness of HRVTs as promising, accessible, and cost-effective means for exercise and clinical prescription purposes.

Cross Polarization in anisotropic Gaussian light beams is derived within the framework of the Maxwell optics using the elegant Mukunda–Simon–Sudarshan matrix substitution rule for transition from Helmholtz scalar wave optics to the Maxwell vector wave optics. It is seen that the electromagnetic field components have certain interesting relations to each other. Other properties such as the intensity distribution are also presented. [ABSTRACT FROM AUTHOR]

The primary purpose of the current investigation was to perform an intensity distribution analysis of a collegiate cross-country (CC) competition, with a secondary purpose to compare race times (RT) with modeled performance times (MPT). Participants completed an incremental treadmill test to determine gas exchange threshold (GET), while the three-minute all-out test was conducted on a 400 m outdoor track to determine critical velocity (CV) and D prime (D′). GET and CV were used as physiological markers for the intensity zones based on heart rate (HR) and running velocity (RV), while CV and D′ were used to determine modeled performance times. Participants wore a Global Positioning System (GPS) watch and heart rate (HR) monitor during competition races. Statistically, less time was spent in HR Zone 1 (12.1% ± 13.7%) compared to Zones 2 (37.6% ± 30.2%) and 3 (50.3% ± 33.7%), while a statically greater amount of time was spent in RV Zone 2 (75.0% ± 20.7%) compared to Zones 1 (8.4% ± 14.0%) and 3 (16.7% ± 19.1%). RTs (1499.5 ± 248.5 seconds (s)) were statistically slower compared to MPTs (1359.6 ± 192.7 s). The observed differences in time spent in each zone are speculated to be related to the influence of environmental conditions on internal metrics and difference in the kinetics of HR and running velocity. Differences in RTs and MPTs are likely due to the MPT equation modeling all-out performance and not considering race strategies. [ABSTRACT FROM AUTHOR]

Purpose: To describe the training volume, intensity distribution, and use of swimming styles during a Paralympic cycle in a multiple swimming champion with paraplegia. Methods: The female Paralympic swimmer was 23–26 years of age and had a body mass of 60 to 62 kg and a body height of 174 cm. She has a spinal cord injury at the Th6 level, competed in the S5/SB4 Para swimming classes, and uses a wheelchair for mobility. Training time, as well as distance in the different intensity zones and swimming styles, was registered with the "workouts for swim coaches" software throughout a full Paralympic cycle. Results: The Para swimmer performed a total of 388, 524, 471, and 656 annual hours of swimming, corresponding to 1126, 1504, 1463, and 1993 km, in the 2012–13, 2013–14, 2014–15, and 2015–16 seasons, respectively. In addition, she performed 1 to 3 weekly dry-land strength sessions and 4 to 6 weekly dry-land basic skill sessions. She conducted 91% to 94% of the swimming distance in each macrocycle at low intensity, 2% to 4% at moderate intensity, and 3% to 6% at high intensity. She performed 78% to 84% of the swimming distance in each macrocycle in the freestyle swimming technique and the remaining 16% to 22% in the backstroke, breaststroke, and butterfly techniques. Conclusion: This case study exemplifies how a female Paralympic swimmer with paraplegia progressed her training in the seasons leading up to the Paralympic Games, reaching an annual training distance of 2000 km, which is similar to that of able-bodied swimmers. [ABSTRACT FROM AUTHOR]

Abstract Background Exercise intensities are prescribed using specific intensity zones (moderate, heavy, and severe) determined by a ‘lower’ and a ‘higher’ threshold. Typically, ventilatory (VT) or blood lactate thresholds (LT), and critical power/speed concepts (CP/CS) are used. Various heart rate variability-derived thresholds (HRVTs) using different HRV indices may constitute applicable alternatives, but a systematic review of the proximity of HRVTs to established threshold concepts is lacking. Objective This systematic review aims to provide an overview of studies that determined HRVTs during endurance exercise in healthy adults in comparison with a reference VT and/or LT concept. Methods A systematic literature search for studies determining HRVTs in healthy individuals during endurance exercise and comparing them with VTs or LTs was conducted in Scopus, PubMed and Web of Science (until January 2022). Studies claiming to describe similar physiological boundaries to delineate moderate from heavy (HRVTlow vs. VTlow and/or LTlow), and heavy from severe intensity zone (HRVThigh vs. VThigh and/or LThigh) were grouped and their results synthesized. Results Twenty-seven included studies (461 participants) showed a mean difference in relative HR between HRVTlow and VTlow of − 0.6%bpm in weighted means and 0.02%bpm between HRVTlow and LTlow. Bias between HR at HRVTlow and VTlow was 1 bpm (limits of agreement (LoA): − 10.9 to 12.8 bpm) and 2.7 bpm (LoA: − 20.4 to 25.8 bpm) between HRVTlow and LTlow. Mean difference in HR between HRVThigh and VThigh was 0.3%bpm in weighted means and 2.9%bpm between HRVThigh and LThigh while bias between HR at HRVThigh and VThigh was − 4 bpm (LoA: − 17.9 to 9.9 bpm) and 2.5 bpm (LoA: − 12.1 to 17.1 bpm) between HRVThigh and LThigh. Conclusion HRVTlow seems to be a promising approach for the determination of a ‘lower’ threshold comparable to VTlow and potentially for HRVThigh compared to VThigh, although the latter needs further empirical evaluation. LoA for both intensity zone boundaries indicates bias of HRVTs on an individual level. Taken together, HRVTs can be a promising alternative for prescribing exercise intensity in healthy, male athletes undertaking endurance activities but due to the heterogeneity of study design, threshold concepts, standardization, and lack of female participants, further research is necessary to draw more robust and nuanced conclusions.

Watts, SP, Binnie, MJ, Goods, PSR, Hewlett, J, Fahey-Gilmour, J, and Peeling, P. Demarcation of intensity from 3 to 5 zones aids in understanding physiological performance progression in highly trained under-23 rowing athletes. J Strength Cond Res 37(11): e593-e600, 2023--The purpose of this investigation was to compare 2 training intensity distribution models (3 and 5 zone) in 15 highly trained rowing athletes (n58 male; n57 female; 19.461.1 years) to determine the impact on primary (2,000-m single-scull race) and secondary (2,000-m ergometer time trial, peak oxygen consumption [V̇O2peak], lactate threshold 2 [LT2 power]) performance variables. Performance was assessed before and after 4 months training, which was monitored through a smart watch (Garmin Ltd, Olathe, KS) and chest-strap heart rate (HR) monitor (Wahoo Fitness, Atlanta, GA). Two training intensity distribution models were quantified and compared: a 3-zone model (Z1: between 50% V̇O2peak and lactate threshold 1 (LT1); Z2: between LT1 and 95% LT2; Z3: .95% LT2) and a 5-zone model (T1-T5), where Z1 and Z3 were split into 2 additional zones. There was significant improvement in LT2 power for both male (4.08% 6 1.83, p, 0.01) and female (3.52% 6 3.38, p 5 0.02) athletes, with male athletes also demonstrating significant improvement in 2,000-m ergometer time trial (2.3% 6 1.92, p 5 0.01). Changes in V̇O2peak significantly correlated with high-quality aerobic training (percent time in T2 zone; r5 0.602, p 50.02), whereas changes in LT2 power significantly correlated with "threshold" training (percent time in T4 zone; r50.529, p50.04). These correlations were not evident when examining intensity distribution through the 3-zone model. Accordingly, a 5-zone intensity model may aid in understanding the progression of secondary performance metrics in rowing athletes; however, primary (on-water) performance remains complex to quantify. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the factors associated with underperformance and the subsequent changes in training characteristics and supportive actions when returning to the world's best cross-country skier. Methods: The participant is the most decorated winter Olympian, with 8 Olympic gold medals, 18 World Championship titles, and 114 World Cup victories. Training data were categorized by training form (endurance, strength, and speed); intensity (low, moderate, and high); and mode (running, cycling, and skiing/roller skiing). In addition, test data were retrospectively analyzed, and interviews were performed with the participant and her support team. Results: After the competitive season, the participant had 8 weeks without systematic training and an evaluation process aiming to detect the factors contributing to underperformance. Here physiological, technical, and psychological challenges were detected. As a consequence, the participant included less high-intensity training (1.2 vs 2.1 sessions/wk, P =.011); more moderate-intensity training (0.9 vs 0.4 sessions/wk, P =.016); and more low-intensity training (6.9 vs 5.9 sessions/wk, P =.036) during the general preparation phase but with similar total endurance training load as previous season. In addition, more strength training (1.6 vs 1.1 h/wk, P =.036) and new ski-specific strength exercises were included. Finally, the athlete's autonomy when planning and adjusting training was increased, nontraining stressors were reduced, more frequent testing was included, systematic mental training was initiated, her nutritional strategy was adjusted, and her asthma treatment was optimized. Conclusions: Overall, the current case study could be used as a framework for the holistic approach to treating an overtraining condition and for generation of new hypothesis in this exiting area. [ABSTRACT FROM AUTHOR]

An index of heart rate variability (HRV), detrended fluctuation analysis (DFA a1) has gathered interest as a surrogate marker of exercise intensity boundaries. The aim of this report was to examine heart rate variability threshold (HRVT) behavior across different ramp incremental (RI) slopes. Seventeen participants completed a series of three RI (15, 30, and 45 W · min−1 slopes) with monitoring of gas exchange parameters, heart rate (HR) and HRV. HRVT1 was defined as the V̇O2 or HR at which DFA a1 reached 0.75 and the HRVT2 at which these values reached 0.5. HRVTs were compared by Pearson's r, Bland–Altman analysis, ICC3,1, ANOVA, and paired t‐testing. An excellent degree of reliability was seen across all three ramps, with an ICC3,1 of 0.93 and 0.88 for the HRVT1 V̇O2 and HR, respectively, and 0.90 and 0.92 for the HRVT2 V̇O2 and HR, respectively. Correlations between HRVT1/2 of the individual ramps were high with r values 0.84–0.95 for both HR and V̇O2. Bland–Altman differences ranged between −1.4 and 1.2 mL · kg−1 · min−1 and −2 and +2 bpm. Paired t‐testing showed no mean differences between any HRVT1/2 ramp comparisons. Cycling ramp slope does not appear to affect either HRVT1 or HRVT2 in terms of HR or V̇O2. [ABSTRACT FROM AUTHOR]

Background: Exercise intensities are prescribed using specific intensity zones (moderate, heavy, and severe) determined by a 'lower' and a 'higher' threshold. Typically, ventilatory (VT) or blood lactate thresholds (LT), and critical power/speed concepts (CP/CS) are used. Various heart rate variability-derived thresholds (HRVTs) using different HRV indices may constitute applicable alternatives, but a systematic review of the proximity of HRVTs to established threshold concepts is lacking. Objective: This systematic review aims to provide an overview of studies that determined HRVTs during endurance exercise in healthy adults in comparison with a reference VT and/or LT concept. Methods: A systematic literature search for studies determining HRVTs in healthy individuals during endurance exercise and comparing them with VTs or LTs was conducted in Scopus, PubMed and Web of Science (until January 2022). Studies claiming to describe similar physiological boundaries to delineate moderate from heavy (HRVTlow vs. VTlow and/or LTlow), and heavy from severe intensity zone (HRVThigh vs. VThigh and/or LThigh) were grouped and their results synthesized. Results: Twenty-seven included studies (461 participants) showed a mean difference in relative HR between HRVTlow and VTlow of − 0.6%bpm in weighted means and 0.02%bpm between HRVTlow and LTlow. Bias between HR at HRVTlow and VTlow was 1 bpm (limits of agreement (LoA): − 10.9 to 12.8 bpm) and 2.7 bpm (LoA: − 20.4 to 25.8 bpm) between HRVTlow and LTlow. Mean difference in HR between HRVThigh and VThigh was 0.3%bpm in weighted means and 2.9%bpm between HRVThigh and LThigh while bias between HR at HRVThigh and VThigh was − 4 bpm (LoA: − 17.9 to 9.9 bpm) and 2.5 bpm (LoA: − 12.1 to 17.1 bpm) between HRVThigh and LThigh. Conclusion: HRVTlow seems to be a promising approach for the determination of a 'lower' threshold comparable to VTlow and potentially for HRVThigh compared to VThigh, although the latter needs further empirical evaluation. LoA for both intensity zone boundaries indicates bias of HRVTs on an individual level. Taken together, HRVTs can be a promising alternative for prescribing exercise intensity in healthy, male athletes undertaking endurance activities but due to the heterogeneity of study design, threshold concepts, standardization, and lack of female participants, further research is necessary to draw more robust and nuanced conclusions. [ABSTRACT FROM AUTHOR]

The longitudinal distributions of the maximum intensity in Bessel light beams (BLBs) of various orders are compared with analogous distributions in Gaussian and Laguerre-Gaussian light beams of the corresponding orders. The concept of a "dangerous zone" of the BLB is introduced. A method for determining its length is proposed. The maximum intensity I0 of the initial Gaussian or Laguerre-Gaussian light beam is initially chosen not to exceed the optical damage threshold of the optical elements and objects used. The dangerous zone of the BLB is the region of space behind the axicon in which the maximum intensity in the BLB exceeds I0. The length of the dangerous zone is taken to be the largest distance zK behind the axicon for which the maximum intensity in the BLB cross section is equal to I0. Additionally, the distance zE from the axicon at which the intensity on the BLB axis and in its peripheral annular field are aligned is determined. The maximum intensity in this cross section in BLBs of the 0th, 1st, and 2nd orders are guaranteed to be less than I0 although the transverse size of the light beam is not yet too large. The relative (in units of the BLB existence length zwI) values of zE and zK for the zero and higher (from the 1st to the 9th) orders of the BLB are calculated with the help of mathematical modeling methods. It is advisable to place objects with low optical damage thresholds at distances greater than zK when designing optical systems using the conical BLB geometry. The 1st order BLB in the region from zK to zE is the most energy efficient for the same given radius of the initial Laguerre-Gaussian beam in terms of the level I0/e2. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study was to evaluate generalization ability of segmentation accuracy for limited FOV CBCT in the male pelvic region using a full‐image CNN. Auto‐segmentation accuracy was evaluated using various datasets with different intensity distributions and FOV sizes. Methods: A total of 171 CBCT datasets from patients with prostate cancer were enrolled. There were 151, 10, and 10 CBCT datasets acquired from Vero4DRT, TrueBeam STx, and Clinac‐iX, respectively. The FOV for Vero4DRT, TrueBeam STx, and Clinac‐iX was 20, 26, and 25 cm, respectively. The ROIs, including the bladder, prostate, rectum, and seminal vesicles, were manually delineated. The U2‐Net CNN network architecture was used to train the segmentation model. A total of 131 limited FOV CBCT datasets from Vero4DRT were used for training (104 datasets) and validation (27 datasets); thereafter the rest were for testing. The training routine was set to save the best weight values when the DSC in the validation set was maximized. Segmentation accuracy was qualitatively and quantitatively evaluated between the ground truth and predicted ROIs in the different testing datasets. Results: The mean scores ± standard deviation of visual evaluation for bladder, prostate, rectum, and seminal vesicle in all treatment machines were 1.0 ± 0.7, 1.5 ± 0.6, 1.4 ± 0.6, and 2.1 ± 0.8 points, respectively. The median DSC values for all imaging devices were ≥0.94 for the bladder, 0.84–0.87 for the prostate and rectum, and 0.48–0.69 for the seminal vesicles. Although the DSC values for the bladder and seminal vesicles were significantly different among the three imaging devices, the DSC value of the bladder changed by less than 1% point. The median MSD values for all imaging devices were ≤1.2 mm for the bladder and 1.4–2.2 mm for the prostate, rectum, and seminal vesicles. The MSD values for the seminal vesicles were significantly different between the three imaging devices. Conclusion: The proposed method is effective for testing datasets with different intensity distributions and FOV from training datasets. [ABSTRACT FROM AUTHOR]

Abstract An index of heart rate variability (HRV), detrended fluctuation analysis (DFA a1) has gathered interest as a surrogate marker of exercise intensity boundaries. The aim of this report was to examine heart rate variability threshold (HRVT) behavior across different ramp incremental (RI) slopes. Seventeen participants completed a series of three RI (15, 30, and 45 W · min−1 slopes) with monitoring of gas exchange parameters, heart rate (HR) and HRV. HRVT1 was defined as the V̇O2 or HR at which DFA a1 reached 0.75 and the HRVT2 at which these values reached 0.5. HRVTs were compared by Pearson's r, Bland–Altman analysis, ICC3,1, ANOVA, and paired t‐testing. An excellent degree of reliability was seen across all three ramps, with an ICC3,1 of 0.93 and 0.88 for the HRVT1 V̇O2 and HR, respectively, and 0.90 and 0.92 for the HRVT2 V̇O2 and HR, respectively. Correlations between HRVT1/2 of the individual ramps were high with r values 0.84–0.95 for both HR and V̇O2. Bland–Altman differences ranged between −1.4 and 1.2 mL · kg−1 · min−1 and −2 and +2 bpm. Paired t‐testing showed no mean differences between any HRVT1/2 ramp comparisons. Cycling ramp slope does not appear to affect either HRVT1 or HRVT2 in terms of HR or V̇O2.

The primary purpose of the current investigation was to perform an intensity distribution analysis of a collegiate cross-country (CC) competition, with a secondary purpose to compare race times (RT) with modeled performance times (MPT). Participants completed an incremental treadmill test to determine gas exchange threshold (GET), while the three-minute all-out test was conducted on a 400 m outdoor track to determine critical velocity (CV) and D prime (D′). GET and CV were used as physiological markers for the intensity zones based on heart rate (HR) and running velocity (RV), while CV and D′ were used to determine modeled performance times. Participants wore a Global Positioning System (GPS) watch and heart rate (HR) monitor during competition races. Statistically, less time was spent in HR Zone 1 (12.1% ± 13.7%) compared to Zones 2 (37.6% ± 30.2%) and 3 (50.3% ± 33.7%), while a statically greater amount of time was spent in RV Zone 2 (75.0% ± 20.7%) compared to Zones 1 (8.4% ± 14.0%) and 3 (16.7% ± 19.1%). RTs (1499.5 ± 248.5 seconds (s)) were statistically slower compared to MPTs (1359.6 ± 192.7 s). The observed differences in time spent in each zone are speculated to be related to the influence of environmental conditions on internal metrics and difference in the kinetics of HR and running velocity. Differences in RTs and MPTs are likely due to the MPT equation modeling all-out performance and not considering race strategies.

Purpose: To quantify the impact of a polarized distribution of training intensity on performance and fatigue in elite swimmers. Methods: Twenty-two elite junior swimmers (12 males, age = 17 [3] y, and 10 females, age = 17 [3] y) participated in a crossover intervention study over 28 wk involving 2- × 6-wk training periods separated by 6 wk. Swimmers were randomly assigned to a training group for the first period: polarized (81% in zone 1, blood lactate concentration, [La]b ≤ 2 mmol·L−1; 4% in zone 2, 2 mmol·L−1 < [La]b ≤ 4 mmol·L−1; and 15% in zone 3, [La]b > 4 mmol·L−1) or threshold (65%/25%/10%). Before and after each period, they performed a 100-m maximal swimming test to determine performance, maximal [La]b, and oxygen consumption and an incremental swimming test to determine speed corresponding to [La]b = 4 mmol·L−1 (V4 mmol·L−1). Self-reported indices of well-being were collected with a daily questionnaire. Results: Polarized training elicited small to moderately greater improvement than threshold training on 100-m performance (within-group change ± 90% confidence interval: 0.97% ± 1.02% vs 0.09% ± 0.94%, respectively) with less fatigue and better quality of recovery. There was no substantial gender effect. No clear differences were observed in physiological adaptations between groups. Conclusions: In elite junior swimmers, a 6-wk period of polarized training induced small improvements in 100-m time-trial performance and, in combination with less perceived fatigue, forms a viable option for coaches preparing such cohorts of swimmers for competition. [ABSTRACT FROM AUTHOR]

This work presents a macroseismic analysis of the AD 1755 Lisbon Earthquake-Tsunami event by means of the combination of intensity data derived from the EMS-98 scale and the ESI-07 scale (Environmental damage). About 600 records of secondary earthquake environmental effects (EEEs) for the whole Spain have been used to define intensities, focused on the SW portion of the Iberian Peninsula. The Spanish data have been complemented with 308 EEEs records from Portugal. The analyses indicate maximum intensities of X EMS-ESI along the Atlantic margin of the Iberian Peninsula with 76 records of Tsunami environmental effects (TEEs). An important amplification (VIII – VII) occurred all along the Guadalquivir basin and the adjacent Betic front at epicentral distances of 300–700 km. In these zones 55 records of ground effects (ground cracks, Liquefactions and slope movements) are catalogued. In the rest of the territory of the Peninsula the most widespread effects were hydrogeological changes with 505 records in Spain and 196 in Portugal (total 701 records) covering all the intensity levels. Increase of flow discharges in springs and elevation of water level in wells was the common groundwater response to seismic shacking, especially in SW Iberia. In this zone water elevation in wells was between 5 and 3 m and persistent increases of discharges long-lasting (several days to two months). Persistent discharges on springs were linked in 143 cases to important SW-NE crustal faults (e.g., Alentejo-Plasencia Fault). From the Intensity distribution the historic seismic scenarios are explored by means of the development of empirical ShakeMaps. These consider the three classical seismic sources proposed for this earthquake: Gorringe Bank (G); Marques de Pombal Fault (M) and Atlantic delamination beneath the Gulf of Cadiz (C). However, individually these seismic sources are too small and unable to generate the resulting seismic scenario depicted by the intensity map developed in this work, with onshore seismic accelerations (PGA) up to 0.82 g. These acceleration values and the great amplification experienced throughout the Guadalquivir basin (0.34–0.52 g) are only possible considering a combination of the three seismic sources (GMC Source) probably related to shallow subduction or lithospheric delamination beneath SW Iberia and the Gulf of Cadiz. This will suggest an NNE-SSW offshore rupture length of 350–360 km with an overall rupture area of c. 84,500 km2 resulting in an event magnitude 8.6 Mw calculated from empirical relationships. The results demonstrate the efficacy of these kind of approaches for better identifying and modelling seismic sources for historical events. [Display omitted] [ABSTRACT FROM AUTHOR]

Identifying exercise intensity boundaries has been shown to be important during endurance training for performance enhancement and rehabilitation. Unfortunately, even though surrogate markers show promise when assessed on a group level, substantial deviation from gold standards can be present in each individual. The aim of this study was to evaluate whether combining two surrogate intensity markers improved this agreement. Electrocardiogram (ECG) and gas exchange data were obtained from 21 participants who performed an incremental cycling ramp to exhaustion and evaluated for first (VT1) and second (VT2) ventilatory thresholds, heart rate (HR) variability (HRV), and ECG derived respiratory frequency (EDR). HRV thresholds (HRVT) were based on the non-linear index a1 of a Detrended Fluctuation Analysis (DFA a1) and EDR thresholds (EDRT) upon the second derivative of the sixth-order polynomial of EDR over time. The average of HRVT and EDRT HR was set as the combined threshold (Combo). Mean VT1 was reached at a HR of 141 ± 15, HRVT1 at 152 ± 14 (p < 0.001), EDRT1 at 133 ± 12 (p < 0.001), and Combo1 at 140 ± 13 (p = 0.36) bpm with Pearson's r of 0.83, 0.78, and 0.84, respectively, for comparisons to VT1. A Bland–Altman analysis showed mean biases of 8.3 ± 7.9, −8.3 ± 9.5, and −1.7 ± 8.3 bpm, respectively. A mean VT2 was reached at a HR of 165 ± 13, HRVT2 at 167 ± 10 (p = 0.89), EDRT2 at 164 ± 14 (p = 0.36), and Combo2 at 164 ± 13 (p = 0.59) bpm with Pearson's r of 0.58, 0.95, and 0.94, respectively, for comparisons to VT2. A Bland–Altman analysis showed mean biases of −0.3 ± 8.9, −1.0 ± 4.6, and −0.6 ± 4.6 bpm, respectively. Both the DFA a1 and EDR intensity thresholds based on HR taken individually had moderate agreement to targets derived through gas exchange measurements. By combining both non-invasive approaches, there was improved correlation, reduced bias, and limits of agreement to the respective corresponding HRs at VT1 and VT2. [ABSTRACT FROM AUTHOR]

Studies highlight the usage of non-linear time series analysis of heart rate variability (HRV) using the short-term scaling exponent alpha1 of Detrended Fluctuation Analysis (DFA-alpha1) during exercise to determine aerobic and anaerobic thresholds. The present study aims to further verify this approach in women. Gas exchange and HRV data were collected from 26 female participants with different activity levels. Oxygen uptake (VO2) and heart rate (HR) at first (VT1) and second ventilatory thresholds (VT2) were compared with DFA-alpha1-based thresholds 0.75 (HRVT1) and 0.50 (HRVT2). Results: VO2 at VT1 and VT2 were 25.2 ml/kg/min (± 2.8) and 31.5 ml/kg/min (± 3.6) compared with 26.5 ml/kg/min (± 4.0) and 31.9 ml/kg/min (± 4.5) for HRVT1 and HRVT2, respectively (ICC3,1 = 0.77, 0.84; r = 0.81, 0.86, p < 0.001). The mean HR at VT1 was 147 bpm (± 15.6) and 167 bpm (± 12.7) for VT2, compared with 152 bpm (± 15.5) and 166 bpm (± 13.2) for HRVT1 and HRVT2, respectively (ICC3,1 = 0.87, 0.90; r = 0.87, 0.90, p < 0.001). Bland–Altman analysis for VT1 vs. HRVT1 showed a mean difference of − 1.3 ml/kg/min (± 2.4; LoA: 3.3, − 6.0 ml/kg/min) for VO2 and of − 4.7 bpm (± 7.8; LoA: 10.6, − 20.0 bpm) for HR. VT2 vs. HRVT2 showed a mean difference of − 0.4 ml/kg/min (± 2.3; LoA: 4.1, − 4.9 ml/kg/min) for VO2 and 0.5 bpm (± 5.7; LoA: 11.8, − 10.8 bpm) for HR. DFA-alpha1-based thresholds showed good agreement with traditionally used thresholds and could be used as an alternative approach for marking organismic transition zones for intensity distribution in women. [ABSTRACT FROM AUTHOR]

The Debye–Scherrer (DS) technique is a common technique for determining spacings in atomic layers by X-ray diffraction. The spacings of the atomic layers are proportional to the macroscopic stress in the radiated area. When a crystalline powder is irradiated with X-rays, the diffracted X-rays produce a ring that photographic films detect. Afterward, the film is developed to reveal the rings. Earlier, this procedure took lots of time. With upcoming multiple wavelength anomalous dispersion-detectors, a very sensitive area detector, DS rings can be detected and analyzed in minutes. This allows for the rapid determination of residual stresses prior to inspection in a production environment. Additional information from the intensity distribution within the ring can be obtained. A description of the new technique is given.

This study aimed to describe the racing and training demands of the Cape Epic. Six male mountain bike riders (age: 39 ± 7 years, height: 181 ± 3 cm, and body mass: 78.7 ± 8.1 kg) trained for 4.5 months and took part in the Cape Epic. Training and racing data (prologue, stage 1, and 2) were analyzed, and riders were tested in the laboratory on 3 distinct occasions for maximal oxygen uptake (...O2max), maximal work rate (Ẇmax), and power output associated with the respiratory compensation point (RCPPO). Statistical significance was set at p ≤ 0.05. With race durations of 1.5 ± 0.2, 6.5 ± 1.2, and 6.4 ± 1.4 hours for, respectively, prologue, stage 1, and 2, normalized power was higher in prologue (3.73 ± 0.72 W⋅kg-1) compared with stages 1 (3.06 ± 0.59 W⋅kg-1, p < 0.001) and 2 (2.94 ± 0.69 W⋅kg-1, p < 0.001). Riders spent more time in power zones 1 and 2 (as %RCPPO) and less time in zones 4 and 5, during stage 2 compared with prologue (all zones p ≤ 0.028). Despite no changes in ...O2max or Ẇmax, RCPPO increased from midtraining (3.89 ± 0.61 W⋅kg-1) to prerace testing (4.08 ± 0.64 W⋅kg-1, p = 0.048). No differences were found between base and build training phases for time in power zones. In conclusion, the Cape Epic requires an ability to sustain high submaximal power outputs for several hours as well as an ability to repeat high-intensity efforts throughout the race. A well-balanced program, incorporating a pyramidal intensity distribution, maybe used as a starting point for the design of optimal training approaches. [ABSTRACT FROM AUTHOR]

The objectives of this study were to quantify training intensity as a function of time spent in three metabolic intensity zones, to compare programmed intensity, measured intensity (heart rate) and estimated intensity (RPE: Rating Perceived Exertion), and then to determine the training loads in 8 high level male tennis players. No difference was found between the time programmed in zones 1 (69.9 ± 4.8 %) and 2 (22.8 ± 4.4 %) and the time spent at a heart rate below Ventilatory Threshold 1 (VT1) (78.9 ± 9.4 %) and between VT1 and Ventilatory Threshold 2 (VT2) (18.3 ± 9.5 %) (p > 0.05). Thus, they trained in accordance with the programmed and recommended intensity distribution by adopting a "pyramid" pattern of intensity distribution. Furthermore, significant differences were found between the percentages of scheduled time and the percentages of perceived time (RPE) for all zones (p < 0.05). The overestimation of the estimated intensity can be explained by their age and the intermittent nature of tennis. Finally, we can note that the programmed training load is like that observed for players of the same age and level. [ABSTRACT FROM AUTHOR]

• The paper investigates the design and optimization of neutron guide systems, focusing on the effects of collimator length and guide angles on neutron intensity and uniformity. • The study reveals that increasing the collimator length improves the uniformity of neutron intensity distribution at the sample location. For instance, a collimator length of 12 m results in a more uniform intensity across monitors compared to a 1-meter length, where significant variations are noted. • The research compares linear collimators with a combination of diverging and converging collimators. The findings indicate that the combined collimators provide a more uniform neutron intensity distribution than linear collimators. • The angle between neutron guides significantly affects neutron intensity. • The research classifies neutrons into seven energy groups, demonstrating that adjusting the angle can effectively filter out fast and intermediate neutrons, allowing predominantly low-energy neutrons to reach the sample. The present study investigates the effect of some geometrical parameters on the performance of the neutron guide system, including the length of the collimator and the angle between successive guides. This study investigates the use of optical components to remove fast neutrons in straight and angled guides, and their role in focusing the neutron beam and increasing the intensity uniformity on the sample. In this research, the McStas code, which was developed with the Monte Carlo method, was used. The effect of the length of the collimator on the creation of a neutron beam with a certain energy, and the uniformity of the intensity of the beam at the sample location have been investigated. For angled guides, the intensity of the neutron beam and its uniformity at the sample location, in terms of the angle of the guides with each other, were calculated using McStas and Vitess codes and the results were compared with each other. Calculations have been done using an americium-beryllium source with an intensity of about 5 Curie. The results show that the combination of two convergent and divergent collimators have greater ability to uniform the neutron intensity than the linear collimator. [ABSTRACT FROM AUTHOR]

The spatial distribution of the emission intensity in the near field of a laser-diode bar with a wavelength of 808 nm is obtained experimentally. During the experiments, laser diodes operate in the quasi-continuous lasing mode in the range of injection currents from the threshold value to the onset of degradation of individual laser diodes. On the basis of analysis of the distribution of the emission intensity in the near field in the direction parallel to epitaxial layers, a system of parameters is proposed that makes it possible to obtain a probabilistic estimate of the limiting value of the injection current of individual diodes. During optical inspection of the surface of the laser diodes, it is found that the failure of individual diodes in most cases occurs due to catastrophic optical degradation of the semitransparent mirror of a laser cavity formed on the cleaved surface of a semiconductor. The proposed system of parameters includes both previously known and new ones: the ratio of the maximum and average values of the intensity of laser diodes in the spatial distribution, the standard deviation of the intensity, and a parameter that takes into account the emission intensity of edge-emitting laser diodes. As a result of analysis of the spatial distribution of the emission intensity in the near field of a laser-diode bar in the working section of the light–current characteristic, it is possible to single out individual laser diodes characterized by the lowest limiting injection current and to predict the development of degradation processes. [ABSTRACT FROM AUTHOR]

A new source-target mapping for the design of refractive optical elements generating prescribed 2D intensity distributions is proposed. The calculation of the optical element is reduced to the solution of ordinary explicit differential equations. The simulation results presented demonstrate high performance of the proposed method. While generating uniform rectangular intensity distributions with angular dimensions varying from 80°×1° to 40°×20°, the normalized root-mean-square deviations between the generated and required distributions do not exceed 15 %.

In this work, we demonstrate a simple analytical approach to the problem of surface plasmon polaritons excitation with a metallic nanoantenna placed above a metal surface. The method uses the reciprocity theorem and is similar to the calculation of amplitudes of dielectric waveguide modes excited by a current distribution. To maximize clarity of the demonstration, we formulate the problem in a simple two-dimensional geometry. The analytical results are shown to agree well with the numerical solution obtained by finite elements in frequency domain and finite difference in time domain methods.

Identifying exercise intensity boundaries has been shown to be important during endurance training for performance enhancement and rehabilitation. Unfortunately, even though surrogate markers show promise when assessed on a group level, substantial deviation from gold standards can be present in each individual. The aim of this study was to evaluate whether combining two surrogate intensity markers improved this agreement. Electrocardiogram (ECG) and gas exchange data were obtained from 21 participants who performed an incremental cycling ramp to exhaustion and evaluated for first (VT1) and second (VT2) ventilatory thresholds, heart rate (HR) variability (HRV), and ECG derived respiratory frequency (EDR). HRV thresholds (HRVT) were based on the non-linear index a1 of a Detrended Fluctuation Analysis (DFA a1) and EDR thresholds (EDRT) upon the second derivative of the sixth-order polynomial of EDR over time. The average of HRVT and EDRT HR was set as the combined threshold (Combo). Mean VT1 was reached at a HR of 141 ± 15, HRVT1 at 152 ± 14 (p < 0.001), EDRT1 at 133 ± 12 (p < 0.001), and Combo1 at 140 ± 13 (p = 0.36) bpm with Pearson’s r of 0.83, 0.78, and 0.84, respectively, for comparisons to VT1. A Bland–Altman analysis showed mean biases of 8.3 ± 7.9, −8.3 ± 9.5, and −1.7 ± 8.3 bpm, respectively. A mean VT2 was reached at a HR of 165 ± 13, HRVT2 at 167 ± 10 (p = 0.89), EDRT2 at 164 ± 14 (p = 0.36), and Combo2 at 164 ± 13 (p = 0.59) bpm with Pearson’s r of 0.58, 0.95, and 0.94, respectively, for comparisons to VT2. A Bland–Altman analysis showed mean biases of −0.3 ± 8.9, −1.0 ± 4.6, and −0.6 ± 4.6 bpm, respectively. Both the DFA a1 and EDR intensity thresholds based on HR taken individually had moderate agreement to targets derived through gas exchange measurements. By combining both non-invasive approaches, there was improved correlation, reduced bias, and limits of agreement to the respective corresponding HRs at VT1 and VT2.

Based on the data of tornadoes that happened during 2016-2020 and corresponding damage survey data, the present study analyzed the characteristics of tornadoes in China according to the "Enhanced Fujita scale" and the tornado intensity scale proposed by Chinese meteorologists. The main conclusions are as follows: (1) In the past 5 years, we collected 178 tornadoes cases in China. Few EF2 tornadoes or stronger ones were overlooked, which is close to the actual situation; however, EF1 tornadoes and weaker ones may be ignored, so the total number of tornadoes may be significantly underestimated. Tornadoes mainly occurred in the flat areas in eastern China and parts of central China. Weak tornadoes also occurred in the Qinghai-Tibet Plateau and Yunnan Province. Guangdong Province, Jiangsu Province and Anhui Province were the three provinces with the highest frequency of tornado occurrence. 95% of the tornadoes occurred in the areas with a surface roughness length of 0.04~1.70 m, and the underlying land within these areas were mainly used for low-rise crops, farmland, suburbs, bushes, and low-rise buildings. 96% of the tornadoes occurred during 10:00-20:00 BJT from April to September. (2) Based on 39 cases of tornadoes with detailed damage survey, a total of 22 strong tornadoes were confirmed at or above the EF2 scale, 5.5 more than the average number of times every 5 years from 1961 to 2010, among which 5 were EF3 tornadoes, 3 were EF4 tornadoes, and the length and width of the tornadoes path were positively correlated with the strength of the tornado. (3) The ground disaster characteristics of tornadoes in China include: narrow path and strip traces, convergence-like inversion, twisted break, asymmetrical distribution of intensity, obvious projectiles, etc. (4) The live video of the tornado showed the morphological characteristics of the different stages of the development of tornadoes, and for the first time in China, the fact that there are many vortex tornadoes was confirmed, providing valuable data of the structure and evolution of tornadoes. [ABSTRACT FROM AUTHOR]

One year of training data from 8 elite orienteers were divided into a transition phase (TP), general preparatory phase (GPP), specific preparatory phase (SPP), and competition phase (CP). Average weekly training volume and frequency, hours at different intensities (zones 1–3), cross-training, running, orienteering, interval training, continuous training, and competition were calculated. Training volume was higher in GPP than TP, SPP, and CP (14.9 vs 9.7, 11.5, and 10.6 h/wk, P < .05). Training frequency was higher in GPP than TP (10 vs 7.5 sessions/wk, P < .05). Zone 1 training was higher in GPP than TP, SPP, and CP (11.3 vs 7.1, 8.3, and 7.7 h/wk, P < .05). Zone 3 training was higher in SPP and CP than in TP and GPP (0.9 and 1.1 vs 1.6 and 1.5 h/ wk, P < .05). Cross-training was higher in GPP than SPP and CP (4.3 vs 0.8 h/wk, P < .05). Interval training was higher in GPP than TP, SPP, and CP (0.7 vs 0.3 h/wk, P < .05). High-intensity continuous training was higher in GPP than CP (0.9 vs 0.4 h/ wk, P < .05), while competition was higher in SPP and CP than in TP and GPP (1.3 and 1.5 vs 0.6 and 0.3 h/wk, P < .01). In conclusion, these champion endurance athletes achieved a progressive reduction in total training volume from GPP to CP via a shortening of each individual session while the number of training sessions remained unchanged. This decrease in training volume was primarily due to a reduction in the number of hours of low-intensity, non-sport-specific cross-training. [ABSTRACT FROM AUTHOR]

This study investigates rainfall intensity distribution in Way Awi watershed located in Bandar Lampung, and how their impacts on flood peak and flood hydrographs. Hourly rainfall data is examined to obtain design rainfall intensity and rainfall intensity distribution at rainfall duration from three to eight hours. Rainfall-runoff model, i.e. Rational method is used to calculate flood peak while unit hydrograph method is used to develop flood hydrograph. This study shows that in Way Awi watershed 88.3% to 96.4% of 24-hour rain occurs in three to eight hour durations. In addition, rainfall with three hour duration generates the highest flood peak, followed by four hour duration rainfall. When rainfall duration and design rainfall intensity are the same but rainfall intensity distribution is different, generated flood hydrograph may have different flood peak magnitude and timing. Result of this study is useful for flood analysis and mitigation in Way Awi watershed.

Past attempts to define an anaerobic threshold (AnT) have relied upon gas exchange kinetics, lactate testing and field-based evaluations. DFA a1, an index of heart rate (HR) variability (HRV) fractal correlation properties, has been shown to decrease with exercise intensity. The intent of this study is to investigate whether the AnT derived from gas exchange is associated with the transition from a correlated to uncorrelated random HRV pattern signified by a DFA a1 value of 0.5. HRV and gas exchange data were obtained from 15 participants during an incremental treadmill run. Comparison of the HR reached at the second ventilatory threshold (VT2) was made to the HR reached at a DFA a1 value of 0.5 (HRVT2). Based on Bland–Altman analysis and linear regression, there was strong agreement between VT2 and HRVT2 measured by HR (r = 0.78, p < 0.001). Mean VT2 was reached at a HR of 174 (±12) bpm compared to mean HRVT2 at a HR of 171 (±16) bpm. In summary, the HR associated with a DFA a1 value of 0.5 on an incremental treadmill ramp was closely related to that of the HR at the VT2 derived from gas exchange analysis. A distinct numerical value of DFA a1 representing an uncorrelated, random interbeat pattern appears to be associated with the VT2 and shows potential as a noninvasive marker for training intensity distribution and performance status. [ABSTRACT FROM AUTHOR]

In this project, the ISP 51 (Inductively Coupled Plasma) automation was implemented to perform digital calculations. For this, a digital camera was placed in the spectrograph detection area, and all the images obtained were processed using the LabVIEW software environment. [ABSTRACT FROM AUTHOR]

Purpose: The authors directly compared 3 frequently used methods of heart-rate-based training-intensity- distribution (TID) quantification in a large sample of training sessions performed by elite endurance athletes. Methods: Twenty-nine elite cross-country skiers (16 male, 13 female; 25 ± 4 y; 70 ± 11 kg; 76 ± 7 mL • min-1 • kg-1 VO2max) conducted 570 training sessions during a ~14-d altitude-training camp. Three analysis methods were used: time in zone (TIZ), session goal (SG), and a hybrid session-goal/time-in-zone (SG/TIZ) approach. The proportion of training in zone 1, zone 2, and zone 3 was quantified using total training time or frequency of sessions, and simple conversion factors across different methods were calculated. Results: Comparing the TIZ and SG/TIZ methods, 96.1% and 95.5%, respectively, of total training time was spent in zone 1 (P < .001), with 2.9%/3.6% and l.l%/0.8% in zones 2/3 (P < .001). Using SG, this corresponded to 86.6% zone 1 and 1 l.l%/2.4% zone 2/3 sessions. Estimated conversion factors from TIZ or SG/TIZ to SG and vice versa were 0.9/1.1, respectively, in the low-intensity training range (zone 1) and 3.0/0.33 in the high-intensity training range (zones 2 and 3). Conclusions: This study provides a direct comparison and practical conversion factors across studies employing different methods of TID quantification associated with the most common heart-rate-based analysis methods. [ABSTRACT FROM AUTHOR]

The short-term scaling exponent alpha1 of detrended fluctuation analysis (DFA a1), a nonlinear index of heart rate variability (HRV) based on fractal correlation properties, has been shown to steadily change with increasing exercise intensity. To date, no study has specifically examined using the behavior of this index as a method for defining a low intensity exercise zone. The aim of this report is to compare both oxygen intake (VO2) and heart rate (HR) reached at the first ventilatory threshold (VT1), a well-established delimiter of low intensity exercise, to those derived from a predefined DFA a1 transitional value. Gas exchange and HRV data were obtained from 15 participants during an incremental treadmill run. Comparison of both VO2 and HR reached at VT1 defined by gas exchange (VT1 GAS) was made to those parameters derived from analysis of DFA a1 reaching a value of 0.75 (HRVT). Based on Bland Altman analysis, linear regression, intraclass correlation (ICC) and t testing, there was strong agreement between VT1 GAS and HRVT as measured by both HR and VO2. Mean VT1 GAS was reached at 39.8 ml/kg/min with a HR of 152 bpm compared to mean HRVT which was reached at 40.1 ml/kg/min with a HR of 154 bpm. Strong linear relationships were seen between test modalities, with Pearson’s r values of 0.99 (p < 0.001) and.97 (p < 0.001) for VO2 and HR comparisons, respectively. Intraclass correlation between VT1 GAS and HRVT was 0.99 for VO2 and 0.96 for HR. In addition, comparison of VT1 GAS and HRVT showed no differences by t testing, also supporting the method validity. In conclusion, it appears that reaching a DFA a1 value of 0.75 on an incremental treadmill test is closely associated with crossing the first ventilatory threshold. As training intensity below the first ventilatory threshold is felt to have great importance for endurance sport, utilization of DFA a1 activity may provide guidance for a valid low training zone.

The short-term scaling exponent alpha1 of detrended fluctuation analysis (DFA a1), a nonlinear index of heart rate variability (HRV) based on fractal correlation properties, has been shown to steadily change with increasing exercise intensity. To date, no study has specifically examined using the behavior of this index as a method for defining a low intensity exercise zone. The aim of this report is to compare both oxygen intake (VO2) and heart rate (HR) reached at the first ventilatory threshold (VT1), a well-established delimiter of low intensity exercise, to those derived from a predefined DFA a1 transitional value. Gas exchange and HRV data were obtained from 15 participants during an incremental treadmill run. Comparison of both VO2 and HR reached at VT1 defined by gas exchange (VT1 GAS) was made to those parameters derived from analysis of DFA a1 reaching a value of 0.75 (HRVT). Based on Bland Altman analysis, linear regression, intraclass correlation (ICC) and t testing, there was strong agreement between VT1 GAS and HRVT as measured by both HR and VO2. Mean VT1 GAS was reached at 39.8 ml/kg/min with a HR of 152 bpm compared to mean HRVT which was reached at 40.1 ml/kg/min with a HR of 154 bpm. Strong linear relationships were seen between test modalities, with Pearson's r values of 0.99 (p < 0.001) and.97 (p < 0.001) for VO2 and HR comparisons, respectively. Intraclass correlation between VT1 GAS and HRVT was 0.99 for VO2 and 0.96 for HR. In addition, comparison of VT1 GAS and HRVT showed no differences by t testing, also supporting the method validity. In conclusion, it appears that reaching a DFA a1 value of 0.75 on an incremental treadmill test is closely associated with crossing the first ventilatory threshold. As training intensity below the first ventilatory threshold is felt to have great importance for endurance sport, utilization of DFA a1 activity may provide guidance for a valid low training zone. [ABSTRACT FROM AUTHOR]

Exercise and training prescription in endurance-type sports has a strong theoretical background with various practical applications based on threshold concepts. Given the challenges and pitfalls of determining individual training zones on the basis of subsystem indicators (e.g., blood lactate concentration, respiratory parameters), the question arises whether there are alternatives for intensity distribution demarcation. Considering that training in a low intensity zone substantially contributes to the performance outcome of endurance athletes and exceeding intensity targets based on a misleading aerobic threshold can lead to negative performance and recovery effects, it would be desirable to find a parameter that could be derived via non-invasive, low cost and commonly available wearable devices. In this regard, analytics conducted from non-linear dynamics of heart rate variability (HRV) have been adapted to gain further insights into the complex cardiovascular regulation during endurance-type exercise. Considering the reciprocal antagonistic behavior and the interaction of the sympathetic and parasympathetic branch of the autonomic nervous system from low to high exercise intensities, it may be promising to use an approach that utilizes information about the regulation quality of the organismic system to determine training-intensity distribution. Detrended fluctuation analysis of HRV and its short-term scaling exponent alpha1 (DFA-alpha1) seems suitable for applied sport-specific settings including exercise from low to high intensities. DFA-alpha1 may be taken as an indicator for exercise prescription and intensity distribution monitoring in endurance-type sports. The present perspective illustrates the potential of DFA-alpha1 for diagnostic and monitoring purposes as a “global” system parameter and proxy for organismic demands.

Abstract Background Evidence for the importance of accumulating sufficient physical activity in the early years is mounting. This study aimed to determine the relationship between maternal and infant objectively measured physical activity, and to examine the diurnal interactions between these behaviours while accounting for potential covariates. Methods Mothers and infants (n = 152 pairs; infants aged 3–24 months) were recruited from Soweto, South Africa, and physical activity was measured using a wrist worn accelerometer (Axivity AX3, Axivity Ltd., Newcastle-upon-Tyne, UK) for 3–7 days. Mothers completed sleep diaries recording night time-in-bed (used as a proxy for nocturnal sleep status) for themselves and their infant; and reported times during which their infant was in their personal care (caregiver status) for each day during the measurement period. Significant correlates of infant physical activity, as well as the interactions between mother’s physical activity, day of the week, sleep status, and caregiver status, were included in panel regression analyses with infant physical activity as the outcome. Results There was an equal distribution of boys and girls, and their age ranged from 2.6 to 24.5 months. The majority of mothers (73%) did not spend any time apart from their infant. During weekdays, the combined effect of mother’s physical activity (β=0.11), the interactions between mother’s physical activity and caregiver status (β=0.17), and sleep status (β= − 0.04) on infant physical activity was β=0.24; while during weekend days this association was β=0.21; and was largely moderated by the interaction between the mother being with the infant and her activity levels (β=0.23), but partly attenuated by mother’s physical activity independent of other variables (β= − 0.04). For each hour of the day, for both mother and infant, peaks of physical activity were higher when the mother was not the primary caregiver. Conclusions Infant physical activity levels were strongly associated with their mother’s activity levels particularly during the week; this relationship was stronger when mothers were more active while looking after their infant. Mothers should be encouraged to be active when looking after their children, particularly during the week, and to provide infants with as much opportunity to be active as possible.

Exercise and training prescription in endurance-type sports has a strong theoretical background with various practical applications based on threshold concepts. Given the challenges and pitfalls of determining individual training zones on the basis of subsystem indicators (e.g., blood lactate concentration, respiratory parameters), the question arises whether there are alternatives for intensity distribution demarcation. Considering that training in a low intensity zone substantially contributes to the performance outcome of endurance athletes and exceeding intensity targets based on a misleading aerobic threshold can lead to negative performance and recovery effects, it would be desirable to find a parameter that could be derived via non-invasive, low cost and commonly available wearable devices. In this regard, analytics conducted from non-linear dynamics of heart rate variability (HRV) have been adapted to gain further insights into the complex cardiovascular regulation during endurance-type exercise. Considering the reciprocal antagonistic behavior and the interaction of the sympathetic and parasympathetic branch of the autonomic nervous system from low to high exercise intensities, it may be promising to use an approach that utilizes information about the regulation quality of the organismic system to determine training-intensity distribution. Detrended fluctuation analysis of HRV and its short-term scaling exponent alpha1 (DFA-alpha1) seems suitable for applied sport-specific settings including exercise from low to high intensities. DFA-alpha1 may be taken as an indicator for exercise prescription and intensity distribution monitoring in endurance-type sports. The present perspective illustrates the potential of DFA-alpha1 for diagnostic and monitoring purposes as a "global" system parameter and proxy for organismic demands. [ABSTRACT FROM AUTHOR]

Bias field correction is an essential pre‐processing requirement for brain tissue segmentation task. Authentic brain tissue regions are highly useful for classification and detection of abnormalities. A poor resolution magnetic resonance (MR) image is produced with irregularities in structure, abnormalities in the intensity distribution and noise during the acquisition procedure. The existing bias field correction methods do not consider the spatial information. Further, the problem of equidistant pixels while clustering is not addressed. These problems lead to poor segmentation accuracy. To solve these problems, the authors suggest a novel biased fuzzy clustering technique for the problem on hand. The basic idea is to incorporate the spatial information by altering the membership matrix of standard fuzzy C‐means clustering to lower the effect of noise and intensity inhomogeneity. It also helps in improving the segmentation accuracies of the tissue regions by assigning the equidistant pixels to a single cluster. The suggested technique is validated with different modalities of brain MR images. Various evaluation indices are computed followed by the statistical analysis to justify the superiority of the suggested technique in comparison to the state‐of‐the‐art methods. [ABSTRACT FROM AUTHOR]

This article presents a model for simulating the X-ray transmission properties of a polycapillary X-ray lens in which the capillaries are arranged in a layered hexagonal structure. Each layer consists of hexagonally shaped capillary bundles which are arranged symmetrically around a centerline, and the capillary radius varies with the layer. The transmission efficiency of X-rays in different layers is studied, and by designing the capillary radius, a uniform X-ray intensity distribution is generated at the output of the polycapillary parallel X-ray lens, which has remarkable differences with the distribution of a conventional polycapillary parallel X-ray lens. In addition, several common defects in the manufacturing process of the polycapillary lens are simulated. [ABSTRACT FROM AUTHOR]

For the incoherent beam combining system using a concave grating as beam combiner, the methods of the system performance assessment, as well as the grating mount optimization are presented. The system performance assessment reveals that the incoherent combining system can carry out the good spatial overlap results, but the radius of the combined beam in Z-direction is much larger than that in Y-direction due to non-uniform distribution of aberration. The optimization result of the grating mount indicates that the grating should be designed into the mount similar to parabolic, and the maximum aberration along the y-axis is less than 4 ' 10--14 m-1 under the optimized mount structure. [ABSTRACT FROM AUTHOR]

In this paper, we have reported the far-field intensity distribution for a varied configuration of air holes in the cladding region of the solid-core single-mode photonic crystal fibers (PCFs). Recently, an analytical approach based on the normalized frequency (V parameter) and normalized attenuation constant (W parameter) has been developed for index-guided PCF. Parameters V and W are frequently used in the design of conventional optical fibers. Using the empirical relations for the V parameter as well as W parameter of PCF, the dependence of the far-field intensity distribution on two structural parameters—the air hole diameter and the air hole pitch is calculated and presented. The results displayed here can find their utilization in the design and development of a sensor system based on PCFs for potential applications involving structural health monitoring, medicine, environmental monitoring sensors, and in certain areas of biology and chemistry. [ABSTRACT FROM AUTHOR]

Purpose: To examine the effectiveness of threshold and polarized models in the training organization of Chinese top-level sprint speed skaters using a 2-y quasi-experimental design. Methods: Two years (2004-05 and 2005-06 seasons) of the Chinese national speed-skating team's daily training load (N = 9; 5 men, 23.6 ± 1.7 y, weight 76.6 ± 4.1 kg, competitive experience 5.0 ± 0.8 y, 500-m time 35.45 ± 0.72 s, 1000-m time 71.18 ± 2.28 s; 4 women, 25.3 ± 6.8 y, 73.0 ± 8.5 kg, 6.3 ± 3.5 y, 37.81 ± 0.46 s, 75.70 ± 0.81 s) were collected and analyzed. Each season's training load included overall duration (calculated in min and km), frequency (calculated by overall sessions), and training intensity (measured by ear blood lactate or estimated by heart rate), Their performances at national, World Cup, and Olympic competitions during the 2 seasons (2004-06), as well as lactate data measured 15 and 30 min after these competitions, were also collected and analyzed. Based on the lactate data (<2, 2-4, >4 mmol/L), training zones were classified as low, moderate, and high intensity. Results: The total durations and frequencies of the training load were similar across the seasons, but a threshold-training model distribution was used in 2004-05, and a polarized-training-load organization in 2005-06. Under the polarized-training model, or load organization, all speed skaters' performance improved and their lactate after competition decreased considerably. Conclusion: Training-intensity distribution based on a polarized-training model led to the success in top Chinese sprint speed skaters in the 2005-06 season. [ABSTRACT FROM AUTHOR]