Cycling Research Articles

Guiding athletes through heartrate and power based tasks

Background Structured training usually consists of tasks with fixed intensities set by, for example, heart rate or power. Additionally, tests designed for monitoring changes in training status often require athletes to keep their heart rate within one or a few beats of a certain threshold. However, these tasks can be difficult to fulfil, especially for novice athletes and even harder when the boundaries for the targets are narrow. Nevertheless, for reproducibility it is important that tasks are executed in the best possible manner. This pre-study aims to investigate which visual aids can help athletes to achieve better accuracy in their tasks. Method In this study two variants of a novel visual feedback were compared to a classic design showing only numbers. Figure 1 depicts the three variants of the feedback. The first variant (a) visualises the target HR and deviation from it using a horizontal bar while the second variant (b) visualises the same using a Tachometer with the target centred in the middle. The ‘classical design’ (c) visualises the current heart rate or power using a plain number. In order to test the variants a smartphone app was created using the Pegasos-Framework (Dobiasch & Baca, 2016). The app recorded heart rate as well as power and transmitted them to a server in real-time. The test used for the evaluation of the feedback variants is a modified version of the Lambert Submaximal Cycling Test (LSCT) (Lamberts, Swart, Noakes, & Lambert, 2009). The tasks were as follows six minutes at 60% of self-reported maximal heartrate ± two beats, six minutes at 80% ± one beat and three minutes at 90% ± one beat. This was followed by 90 seconds rest. After this a pop up window on the screens tells the participants their target power during the next three minutes stage. During this stage participants were asked to keep their power within ± 10 watts of the target power. This stage was again followed by 90 seconds rest on the bike. Each participant completed three trials each with a different version of the feedback in a randomized order. After each trial participants were asked to out a questionnaire about the used feedback variant. Results 12 participants (8 male, 4 female. Mean ± SD; age: 33.13 ± 12.67 years, height: 178.75 ± 7.56 cm, body mass: 73.12 ± 10.97 kg) participated in the pre-study. Table 1 highlights the results from the heart rate based task. In order to account for the time needed to raise the heart rate to the desired level all measurements are taken starting from one minute into the stage. Two participants were excluded from this analysis due to non-adherence to the protocol or very low accuracy (< 20%). Furthermore, we analysed the relative time spent in the target zone. Due to technical problems, two further trials had to be excluded. Again, no significant differences between the feedback variants were found using a repeated

Relation between maximal power in sprint cycling, pedal force orientation and strength of the lower limb muscles in elite sprint cyclists

The aim of this study was to determine, in a high-level population, how the maximal power produced during pedalling relates to the capacity to orient the pedal force, and to the force-generating capacity of the six main muscle groups of the lower limb, and whether this relationship is improved by using specific velocity conditions during single-joint strength measurements. 19 high-level cyclists performed two separated sessions : first, maximal power during pedalling was assessed while strength capacities were assessed in different force-velocity conditions. Results suggest that assessing single-joint strength at specific velocities is more relevant, and this, particularly in the extension phase. In the flexion phase, the power produced is largely influenced by the capacity to effectively orientate the force on the pedals.

Muscle deoxygenation kinetics in cycling time trial

Background: Concentration changes of oxygenated and deoxygenated haemoglobin (O2Hb and HHb) measured by near infrared spectroscopy (NIRS) provides information about oxygen delivery and extraction at the muscular level. The kinetic response of HHb reflects the adjustment of the oxidative metabolism in skeletal muscle and could therefore be related to exercise tolerance. While most studies used laboratory cycling to investigate the kinetic responses, the effect of cycling time trials in field conditions remains to be shown. Therefore, the aim of this study was to investigate changes in HHb during maximal effort cycling time trials in field conditions. Methods: Thirteen trained cyclists and triathletes (N=13; mean ± SD: age 32 ± 7 years; body mass 74.6 ± 7.4 kg; stature 182 ± 5 cm; maximum oxygen uptake 67.9 ± 3.0 mL·min-1·kg-1; maximal power output 406 ± 39 W), completed 3 cycling time trials lasting 10, 4 and 1 min on a flat road, interspersed by a 30 min recovery period after each trial. Relative changes in HHb were recorded on the right vastus lateralis muscle with a portable continuous-wave NIRS device. Second-by-second data normalised to 100% of the response were used to resolve the amplitude, the time delay and the time constant by nonlinear regression. A repeated measure ANOVA was used to compare the parameter estimates across the time trial durations. Results: The mean power output during the 10-, 4- and 1- minute cycling time trials was 352 ± 45, 385 ± 49 and 525 ± 73 W, respectively (p=0.001). No significant differences were observed for cadence during the 10- vs. 1-minute cycling time trials (p=0.264), however significant differences were observed between 4- vs. 1-minute (p=0.05) The parameter estimates of the kinetic response were significantly affected by time trial duration. The amplitude for 10- vs. 1- minute (78.20 ± 8.42 vs. 89.16 ± 6.82; p = 0.022) as well as for 4- vs. 1-minute (74.99 ± 6.12 vs. 89.16 ± 6.82; p = 0.006) cycling time trial duration showed significant differences. Moreover, significant effects can be reported for the 10- vs. 1-minute time delay parameter (9.54 ± 2.07 s vs. 3.65 ± 1.71s; p = 0.001). Mean response time also demonstrated significant differences for 10- vs. 1-minute cycling time trials (13.45 ± 2.39 s vs. 6.85 ± 1.90 s; p = 0.001). No significant differences were reported for the time constant among the different cycling time trial durations (p>0.05). Discussion: These findings support that the physiological response to high intensity exercise during multiple cycling time trial durations could be monitored by alterations in muscle deoxygenation kinetic parameters. Furthermore, these results imply that changes at the microvascular level are time dependent when exposed to maximal exhaustion. However further research is recommended to support these findings of muscle deoxygenation kinetics during cycling time trial in field conditions.

Muscle deoxygenation during moderate- and severe-intensity cycling in youth elite-cyclists

Background: Near-infrared spectroscopy (NIRS) is a well-established technique to measure tissue oxygenation and haemodynamics during exercise. While muscle oxygen consumption is derived by measuring concentration changes of oxygenated and deoxygenated haemoglobin and myoglobin (O 2 Hb and HHb), total haemoglobin (tHb = O 2 Hb + HHb) reflect blood volume and perfusion. In particular, the change in HHb is considered a proxy for oxygen extraction at the muscle level during exercise and arterial occlusion, where the rate of reoxygenation has been used as a measure of mitochondrial function (Ryan et al, 2012: Journal of Applied Physiology, 113, 175-183). NIRS-derived signals therefore reflect the dynamic balance between oxygen delivery and utilisation and may be important measures to monitor training induced adaptations of aerobic function in skeletal muscle. However, current literature is scarce regarding reliability measures, especially in young athletes, which needs to be established to interpret changes with confidence. Purpose: To assess the test-retest reliability of HHb-changes during moderate- and severe- intensity cycling, and during arterial occlusion in youth elite-cyclists. Methods: Fifteen cyclist (mean ± SD: age 13.5 ± 1.8 y; stature 163.2 ± 12.2 cm; body mass 51.3 ± 12.4 kg; O 2max 62.1 ± 4.2 mL . min -1. kg -1 ) completed two 6-min rest-to-work transitions (T) from baseline (BL: 60 W) to moderate- (90% of the first ventilatory threshold [VT1]: 120 ± 26 W) and to severe- (50% between VT and maximum power [Delta50]: 204 ± 43 W) intensity cycling. The transitions were interspersed by 8 min BL cycling. After Delta50 cycling, an occlusion was applied on the proximal thigh at a pressure of 300 mmHG until a levelling-off of the HHb signal was observed (3-5 min). The protocol was repeated after a passive rest of 1 h. Changes in HHb were measured on the belly of the right vastus lateralis muscle with a portable continuous-wave NIRS device at a sampling rate of 5 Hz (PortaMon, Artinis). Second-per-second data, were corrected for blood volume changes and normalised to the full functional range measured during the occlusion (0-100%). HHb changes (%) were calculated from BL to the maximum of VT1 (I”BL-VT1) and from BL to the maximum of Delta50 (I”BL-Delta50). In addition, the reoxygenation after occlusion was assessed with the slope of linear regression analysis (% . s -1 ). A typical example of the HHb signal is shown in Figure 1. Absolute and relative reliability was calculated with Bland-Altman statistics ± 95% limits of agreement and the coefficient of variation (CV; %), respectively. Paired t-tests were used for comparisons. Results: The I”BL-VT1 was 20.5 ± 11.7 and 21.6 ± 12.3% during T1 and T2, respectively (p = 0.079). The bias was 1.1 ± 2.3 % (95% LoA: -5.6 – 3.3) and the CV 10.1% (7.3 – 16.4). The I”BL-Delta50 were 58.1 ± 9.6 (T1) and 56.5 ± 9.3% (T2) (p = 0.133) and the bias and CV were 1.6 ± 3.9% (-6.0 – 9.3) and 5.4% (3.9 – 8.6), respectively. The reoxygenation slopes were 7.2 ± 2.0 (T1) and 7.6 ± 2.1 % . s -1 (T2) (p = 0.053) with a bias and CV of 0.4 ± 0.7 % . s -1 (-1.8 – 1.0) and 7.0% (5.1 – 11.2), respectively. Discussion: The present study quantified reliability for NIRS-derived changes in HHb during cycling at moderate and severe intensity as well as for reoxygenation after occlusion. The provided levels of 5.4% for severe-intensity cycling and 7.0% for the reoxygenation slope, are well below the level of 10% considered as acceptable for a measurement, and the level of 10.1% for moderate-intensity cycling is only marginally higher. The reliability data established, provide limits within which training induced adaptations may be interpreted with confidence. Longitudinal studies in young athletes could potentially benefit from these findings since the magnitude of changes in NIRS variables is probably greater than the reported measurement error.

Modeling in Road Cycling for Optimal Pacing Strategies : Theory vs. Practice

Introduction: The right choice of a pacing strategy for a time trial race is important and often difficult to establish. With the increasing popularity of online sports data platforms like Strava (www.strava.com), pacing strategies may become interesting even for recreational cyclists since they can compete against each other virtually on selected segments. Methods are now available to generate pacing strategies that are optimal, however, only in a mathematical sense. Until now, they were tested in practice only under laboratory conditions [1]. Pacing strategies are generally based on two mathematical models: (1) to describe the relation between power output and speed [2], and (2) to describe the fatigue of the rider related to the power output [3]. The quality and validity of these pacing strategies relies on the accuracy of the predictions made by those models.In this paper, we describe our findings on a pilot study during a two week period of cycling with regard to the prediction quality of the two models while following precalculated optimal pacing strategies in the field rides. This is not meant to be a fully-fledged study applying, e.g., a statistical analysis for a sufficiently large number of participants. This pilot study rather intended to demonstrate that, in principle, the theoretically optimal pacing strategies can in fact be implemented for field rides in practice. Moreover, it was the purpose of the study to identify the problems of the approach occurring in practice, and to outline solutions for these.Methods: The physiological model is similar to the one used in [1]: an extension of the critical power (CP) concept with reduced recovery. The physical model to predict speed from the rider’s power output is taken from [4]. The optimization of the pacing strategy for an uphill time trial proceeded as in [1]. To calibrate the CP model, four tests were performed in the laboratory for a single hobbyist rider, followed by a number of rides on Strava segments with the goal to achieve personal bests by pursuing the given optimal pacing strategies.The precalculated pacing strategies were communicated during the field rides by means of a custom developed App on a smartphone mounted on the handle bar. Feedback was given numerically, e.g., the current deviation from the optimal speed, and visually by a dash board type gauge. Accumulated deviations from the optimal pacing were attempted to be corrected using a PID control mechanism. These rides were taken to update the parameters of the CP model continually.Results and Discussion: Four rides with optimal feedback were performed on three different Strava Segments. These segments were mainly climbs with a length of 3.5 to 5 km and an average grade from 5.6 to 7 %. The rider’s critical power ranged from 230 to 257 W depending on which tests were used for calibration. The feedback was followed with a root-mean-square error of 0.77 m/s in speed and 48 W in power. Modelling errors and deviations from theoptimal strategy lead to time differences at the end of the segment ranging from 15 s quicker to 100 s slower than the optimal strategy predicted.This discrepancy in time is partly explained by having short downhill parts within the segments and errors in the estimation of the slope profile, which is shown in Figure 1. In the downhill parts, the optimal strategy suggested speeds higher than those during the field ride in which additionally braking was necessary. This error could be reduced by adding a more realistic speed constraint to the optimization and consider braking in the pacing strategy.While the physiological model first was calibrated using tests with a length of about 30 min, the model prediction for the first ride on a shorter segment showed quite poor performance. Adding this segment to the parameter estimation changed the parameters in a way that critical power was reduced and anaerobic capacity increased. With this new parameter set, short as well as mid-range segments were predicted quite well. This shows how important it is to use a range of test durations that covers the future applications.Conclusions: The results showed, that the models work quite well in general and they can be applied to uncontrolled conditions when considering some limitations. Downhill parts are difficult to model and time differences between prediction and ride must be expected in these scenarios. The physiological model needs to be calibrated using segments similar in length and load to the ones that are predicted. With proper model parameter selection and visual feedback with respect to an optimal pacing strategy, significant performance gains for uphill time-trials of hobbyist, amateur, and perhaps also professional athletes can be expected.

Connection between Heel Motion and Torque in crank revolution

In cycling, Torque is made from pedaling. Recently some power meters measure torque in pedaling. Especially Pioneer Power Meter (Pedaling Monitor System - Pioneer Corporation, Tokyo Japan) can measure torque and power in 12 zones in each crank revolution. Using this system, we can easily learn every torque pattern of cyclists are different. Furthermore, we already know ever pedaling of cyclists are different, some of these cyclists have different pedal motion in Left and Right, their L/R balance are different. While in pedaling, forefoot is fixed with cleat, vertical heel motion relative to the pedal angle. From these observations, we can make an assumption that heel motion affects torque. So, this research is carried out in order to find out which heel motion increase torque in a crank revolution.

The new Exposure Variation Analysis (EVA) method to compare pacing strategy and performance during professional time-trial competitions

Abstract: Several studies underlined the impact of pacing strategy on cycling time-trial performance. It has been reported that under steady environmental conditions, maintaining a constant power output (PO) is the most efficient strategy to improve performance (Wells et al. 2013). The Exposure Variation Analysis (EVA) method has recently been proposed to evaluate these pacing strategies, quantifying for an optimal constant pacing strategy the times spent at an accurate PO (APO), at an inappropriate PO (IPO), and the short-time regulations of inappropriate PO (REG) (Ouvrard et al. 2017). It has been demonstrated that increasing time spent at APO and decreasing time spent at IPO allows cyclists to develop higher mean PO and improve performance (Ouvrard et al. 2018. Under review). However, as these indexes are influenced by time-trials course, they were never used to monitor pacing strategies and performance for several time-trials performed by the same cyclists yet. The aim of this study was to analyse the relationships between changes of performance, mean PO and EVA pacing parameters in two professional cyclists during seven official competitive time-trials.  Methods: PO were collected for two professional cyclists (mean VO 2 max 79.0 ± 8.5 mL.min -1 .kg -1 ) during the seven-same time-trials (performed between April 2013 and June 2017 and ranged from 18.7 to 51.6 km). PO fluctuations were analysed from EVA to quantify times spent at APO (PO between 90 and 110 % of mean time-trial PO), IPO (PO lower than 90 % or higher than 110 % of mean PO for more than 10 s) and REG (PO lower than 90 % or higher than 110 % of mean PO for less than 10 s). Relationships between I” meanPO (differences between subject 1 and subject 2 mean PO for each time-trial) and I” meanPO% (differences between subject 1 and subject 2 mean PO, each expressed as a percentage of the subject’s record PO on the time trial duration) and I” APO (differences between subject 1 and subject 2 times spent at APO), I” IPO (differences between subject 1 and subject 2 times spent at IPO), and I” REG (differences between subject 1 and subject 2 REG) were assessed thanks to Pearson correlation coefficients.  Results: I” meanPO ranged from -24 to +39 W for similar physical potentials (20-min record PO 432 vs 428 W). A trend to a negative relationship was identified between I” meanPO and I” IPO (r = -0.70, p = 0.08). Stronger and significant relationships were identified between I” meanPO% and I” IPO (r = -0.94, p = 0.002) and I” APO (r = 0.86, p = 0.01, Figure 1).  Discussion: The main finding of this study is that, when comparing two cyclists during several time-trials, changes of EVA pacing parameters were related to changes of cyclists’ ability to develop high mean PO. The more the cyclists were able to decrease their time spent at IPO and increase their time spent at APO, the more they had a maximal use of their physical capacity during the time-trial, allowing them to develop higher mean PO expressed as a percentage of their record PO. These results are in accordance with Wells et al. (2013), who demonstrated that maintaining a constant PO, and thus increasing time spent at APO, is optimal for time-trial performance under steady environmental conditions. Conversely, increasing PO variations, and consequently time spent at IPO or REG, reflect poor adherence to constant speed, increasing biomechanical losses or fatigue.  Conclusion: EVA seems to be a valuable method to monitor pacing and performance changes for two cyclists during several time-trials.  Values of times spent at IPO and APO can be compared between cyclists to determine if their pacing strategy were optimal to achieve the best performance possible.

Comprehensive comparison of different saline water irrigation strategies for tomato production: Soil properties, plant growth, fruit yield and fruit quality

Saline water has been increasingly used for crop production in areas characterized by freshwater shortage. However, continuous irrigation with saline water often results in adverse effects on the soil-crop system. In this study, we investigated the effects of different saline water irrigation strategies on soil properties, tomato plant growth, fruit yield and fruit quality. The irrigation treatments included (i) continuous irrigation with freshwater (FI), (ii) continuous irrigation with saline water (SI), (iii) irrigation with the saline water blended with freshwater (BI), (iv) irrigation alternately with saline water and freshwater (AI), and (v) irrigation with freshwater at early sensitive stages combined with saline water at later tolerant stages (CI). Overall, saline water irrigation adversely affected the soil-crop system by increasing pH, electrical conductivity, salt ions (Na+, Cl− and SO42-) and sodium adsorption ratio in soils and Na+ in plant tissues, and by decreasing K+/Na+ in both soils and plant tissues, the relative growth rates of plant height and leaf area, plant biomass and fruit yield (compare SI versus FI). However, these adverse effects of saline water on the soil-crop system were generally alleviated by the BI, AI and CI treatments compared to the SI treatment. Despite this, there was no distinct difference in soil properties among the BI, AI and CI treatments. The AI treatment generally showed higher fruit yield as compared to the BI and CI treatments, and even no significant difference as compared to the FI treatment in two out of three cropping seasons. In addition, the AI treatment significantly increased vitamin C, soluble sugar and solids, glucose, fructose and sucrose in tomato fruits as compared to the FI treatment. Our results suggested that the alternate irrigation (AI) was more efficient than the blending (BI) and cycling (CI) irrigation in alleviating the adverse effects of saline water on the soil-crop system.

Study on proliferation effects of low intensity pulsed ultrasound on human bone marrow mesenchymal stem cells in vitro

Objective To investigate the effect of low intensity pulsed ultrasound (LIPUS) on the proliferation of human bone marrow mesenchymal stem cells (hBMSCs) and the effect of Cyclin D1 on the proliferation of hBMSCs induced by LIPUS. Methods The cells were inoculated on the a 12-well culture culture plate at a cell concentration of 2.0×104 cells/ml, LIPUS with radiation intensity of 0, 30, 40, 50, 60 and 80 mW/cm2 was used to stimulate for 5 min, the morphological changes of the cells were observed at 0, 24, 72 and 96 h, cell counting was performed with a Scepter 2.0 handheld cell counter, the cell cycle and value-added index were measured by flow cytometry, the cell proliferation was detected by cell counting kit-8 (CCK-8). The expression of Cyclin D1 was detected by Western blotting. The expression of Cyclin D1 mRNA was detected by reverse transcriptase-polymerase chain reaction (RT-PCR). Results Cell counts were found except for the 30 mW/cm2 (P=0.871) group that the number of cells in 40 W/cm2 (P=0.006), 50 W/cm2 (P=0.001), 60 W/cm2 (P=0.001), 80 W/cm2 (P=0.004) group was significantly higher than that in control group. Cell proliferation assay was found that the proliferation of 30 mW/cm2 (P=0.042), 40 W/cm2 (P=0.012), 50 W/cm2 (P=0.001), 60 W/cm2 (P=0.001), 80 W/cm2 (P=0.046) cells was significantly higher than that of the control group. Flow cytometry detection found that the cell proliferation index of LIPUS group was significantly higher than that of control group (P=0.001). Western blotting and RT-PCR showed that there was no significant difference between the 30 mW/cm2 group and the control group. The expression of Cyclin D1 was significantly increased in 40 W/cm2 (P=0.002), 50 W/cm2 (P=0.004), 60 W/cm2 (P=0.023), 80 W/cm2 (P=0.012) groups. The expression of Cycling D1 mRNA was significantly different from that of control group (P=0.001). Conclusion LIPUS can significantly promote the proliferation of hBMSCs, and promote the proliferation of hBMSCs from G1 phase to S phase by up-regulation of Cyclin D1 expression. Key words: Low intensity pulsed ultrasound; Human bone marrow mesenchymal stem cells; Proliferation; Cyclin D1

Can you go the extra mile? : the effect of ego depletion on endurance performance

We tested the assumption, that individuals (N = 13 participants) would perform worse in a cycling endurance task and would invest less effort under ego depletion than with temporarily available self-control strength. Participants' self-control strength was experimentally manipulated (non-depletion vs ego depletion, order counterbalanced) in a within-subjects design (two points of measurement, 48 hours apart) before participants performed a 6 km time trial on an indoor track. Non-parametric bootstrapping revealed that ego depletion had the most obvious effect on power output and cycling times per lap at the beginning of the time-trial. The effect of ego depletion on revolutions per minute and heart rate was large in the early parts of the time-trial, faded somewhat during the middle, while it increased again towards the end of the time-trial. The current study suggests that it might be beneficial to develop strategies which help to replenish depleted self-control strength.

Cycling into Headwinds

Cycling into Headwinds

Vastly Different Exercise Programs Similarly Improve Parkinsonian Symptoms: A Randomized Clinical Trial

Objectives: To directly compare the effects of agility exergaming (EXE) and stationary cycling (CYC) exercise training on Parkinson’s disease (PD) patients’ mobility and clinical symptoms. Design: Randomized clinical trial. Setting: Outpatient physiotherapy clinic in a hospital. Participants: Seventy-four stage 2–3, nondemented PD patients were included in this study. Intervention: The groups were as follows: EXE (n = 25), CYC (n = 25), and a wait-listed control group (CON; n = 24). The EXE and CYC groups exercised 5×/week for 5 weeks, matched at 80% of the age-predicted maximal heart rate. Main Outcomes: The primary outcome was the Movement Disorders Society Unified Parkinson’s Disease Rating Scale (UPDRS-II) score. Secondary outcomes were Parkinson’s Disease Quastionnaire-39 (PDQ-39), the Beck Depression Inventory (BDI), the Schwab and England Activities of Daily Living (SE-ADL) scale, Euro-Quality of Life-5 Dimensions (EQ-5D) questionnaire, the Berg Balance Scale (BBS), the Balance Evaluation Systems Test (BESTest), the Tinetti Assessment Tool (TAT), the Dynamic Gait Index, the 6-min walk test (6MWT), and standing posturography. Results: After treatment, UPDRS-II scores improved (mean change: EXE, –4.5 points; CYC, –3.2 points). The results for the other outcomes (EXE and CYC, respectively) were: PDQ, 13 and 17%; BDI, –2.5 and –2.1 points; 6MWT, 129.6 and 141.6 m; and EQ-5D, 12 and 9% (all p < 0.05, but there was no difference between groups). EXE vs. CYC resulted in improved SE-ADL (8.4 and 4.0 points, effect size [ES]: 0.12), BBS (8.8 and 4.2 points, ES: 0.44), and 2 measures of posturography (ES: 0.11 and 0.21) (p < 0.05). BESTtest, TAT, the Dynamic Gait Index, and 4 out of 6 posturography measures did not change (p > 0.05). Conclusion: Two highly different exercise programs resulted in similar improvement of most motor and clinical symptoms in PD patients.

The effect of nursing based on PDCA circulation mode on risk control in digestive endoscopy

Objective To explore the effect of PDCA cycling on risk control in digestive endoscopy. Methods From February 2015 to February 2017, 751 patients requiring digestive endoscopy were selected in the gastroscopy room of the department of gastroscopy in the hospital. According to the different nursing patterns around April 2016, 373 cases were divided into the observation group and 378 cases were divided into the control group, and they were respectively given nursing and routine nursing based on PDCA model. The nursing quality score (score of basic nursing quality, score of specialized nursing quality, score of disinfection nursing quality, score of skilled operation nursing quality), the incidence of nursing defects(non-standard asepsis requirements, lack of cleaning strength, disorderly placement of instruments, and tedious inspection and waiting) and nursing satisfaction (very satisfied, more satisfied, generally satisfied, dissatisfied) were compared between the two groups. Results In terms of the quality of patients' care, the total score of the patients of the quality of basic care in the observation group was (96.21±4.25), the score of quality of specialist care was (93.27±3.52), the quality score of disinfection and isolation care was(98.23±3.72), the score of skill operation and nursing quality was(97.31±3.14). While the total score of the patients of the quality of basic care in the control group was (83.71±4.26), the score of quality of specialist care was(84.31±3.17), the quality score of disinfection and isolation care was(89.12±4.06), the score of skill operation and nursing quality was(80.52±4.24). The nursing group based on PDCA circulation mode had higher quality of care than the conventional nursing group, and the difference was statistically significant(P<0.05). In terms of the incidence of patients' nursing defects, the nursing defect rate of sterile requirement of the observation group was 10.10%, the washout strength insufficient nursing defect rate was 13.70%, the instrument placement disorder incidence was 11.30%, the check wait complication rate was 10.00%. The nursing defect rate of sterile requirement of the control group was 19.00%, the washout strength insufficient nursing defect rate was 25.10%, the instrument placement disorder incidence was 21.40%, the check wait complication rate was 24.10%.Nursing defect rate of patients in the nursing group based on PDCA circulation mode was lower than that in the conventional nursing group, and the difference was statistically significant(P<0.05). In terms of patients' satisfaction, the very satisfaction rate of the observation group was 32.40%, the comparative satisfaction rate was 37.80%, the satisfaction rate was 18.80%, the dissatisfaction rate was 11.00%. The very satisfaction rate of the control group was 19.80%, the comparative satisfaction rate was 18.30%, the satisfaction rate was 34.10%, the dissatisfaction rate was 28.60%.Compared with the conventional nursing group, the patients in the PDCA cycle group had better satisfaction, and the difference was statistically significant(P<0.05). Conclusion In terms of risk control of digestive endoscopy, nursing based on PDCA cycle mode can improve nursing quality, improve patients' satisfaction and reduce the incidence of complications, which is obviously superior to conventional nursing. Key words: Nursing based on PDCA circulation mode; Gastrointestinal endoscopy; Risk control

A UK and Partisan view of Brexit and Dental Public Health.

I walked to work on 24th June 2016, reeling from the news that the UK referendum had shown a small but decisive majority in favour of leaving the European Union. I only knew of one person who had voted for Brexit! I had seen a few Leave posters up whilst out cycling and the opinion polls showed only a small difference, but none the less, I was hugely surprised. A neighbour reassured me that a deal would be struck so that we would fi nd a nice arrangement amounting to a modest change, but the last two years have shown the value of his insights.

Effect of Bioactive Composites on Microhardness of Enamel Exposed to Carious Challenge.

This study verified if experimental composites containing calcium phosphate nanoparticles exert a protective effect against enamel demineralization. Three experimental resin-based composites containing 60 vol% of fillers were manipulated. Filler phase was constituted by silanized barium glass and 0%, 10% or 20% (by volume) of dicalcium phosphate dihydrate (DPCD) nanoparticles functionalized with the monomer triethylene glycol dimethacrylate (TEGDMA). Cavities (10 x 2 x 2 mm) were prepared in bovine enamel and restored using one of the experimental materials (n=10). Specimens were exposed to pH cycling (demineralizing solution: pH 5.0/4h, remineralizing solution: pH 7.0/20h, 14 days). Enamel Knoop microhardness (100g/10s) was measured on the surface (SH) and after transversal sectioning up to 90 μm depth (cross-sectional microhardness, CSH). Microhardness values and the percent of microhardness loss were analyzed ANOVA/Tukey test and Student's paired t-test (alpha: 5%). The materials did not differ in respect to SH. Enamel adjacent to DCPD-containing composite restorations showed smaller reductions in CSH (-1.2% to -3.5%) than the enamel from control group (-12.5%), while CSH of enamel restored with resin-modified glass ionomer was similar to the other groups (-4.5%). DCPD-containing composites reduced enamel demineralization in comparison to a conventional composite.

Pathway Analysis of Phenol Degradation by UV/TiO2 Photocatalysis Utilising the C-13 Isotopic Labelling Technique

Photocatalysis is a green technology for the degradation of persistent organic compounds in water and has been successful in the removal of several water pollutants. Degradation of organic compounds in water is often accompanied by the formation of several intermediate compounds, some of which are feared to be more toxic than the original compound being treated. In this study, aromatic intermediates formed during the photocatalytic degradation of phenol were profiled in a batch system. The carbon-13 isotopic labelling technique was used to track the degradation pathway. Photocatalytic degradation of phenol was conducted in 1L solutions of phenol (20mg/L) in ultrapure water in a batch system. Catalyst concentration was constant at 8mg/L Titanium dioxide (TiO2). Concentration of phenol and detection of the aromatic intermediates of phenol degradation were monitored on a Waters High Performance Liquid Chromatograph (HPLC) and Gas Chromatogram- Mass Spectrometer (GC-MS), respectively. Aromatic intermediates identified during the course of photocatalysis of the phenol include hydroquinone, benzoquinone catechol and resorcinol. The concentration of phenol was determined from the calibration curve of standards of phenol. Photocatalysis is a promising technology for the complete mineralization of aromatic organic pollutants as it has been demonstrated that both the pollutant and its direct intermediates can be completely removed from solution. Phenol degradation produces first aromatic dihydroxy substituted compounds that are further degraded forming cycling compounds on cleavage of the aromatic ring. The distribution of the degradation intermediates confirms that the dominant degradation pathway is via hydroxyl radical mechanism.

Lifetime prediction of optocouplers in digital input and output modules based on bayesian tracking approaches

Digital input and output modules are widely used to connect digital sensors and actuators to automation systems. Digital I/O modules provide flexible connectivity extension to numerous sensors and actuators and protect systems from high voltages and currents by isolation. Components in digital I/O modules are inevitably affected by operating and environmental conditions, such as high voltage, high current, high temperature, and temperature cycling. Because digital I/O modules transfer signals or isolate the systems from unexpected voltage and current transients, their failures may result in signal transmission failures and damages to sensitive circuitry leading to system malfunction and system shutdown. In this study, the lifetime of optocouplers, one of the critical components in digital I/O modules, was predicted using Bayesian tracking approaches. Accelerated degradation tests were conducted for collecting the critical performance parameter of optocouplers, current transfer ratio (CTR), during their lifetime. Bayesian tracking approaches, including extended Kalman filter and particle filter, were applied to predict the failure. The performance of each prognostic algorithm was then compared using accuracy and robustness-based performance metrics.

Modeling the Dynamic Vegetation–Climate System over China Using a Coupled Regional Model

AbstractUsing the Regional Climate Model (RegCM) coupled with the Community Land Model (CLM) including modules of carbon–nitrogen cycling (CN) and vegetation dynamics (DV), this study evaluates the performance of the model with different capacity of representing vegetation processes in simulating the present-day climate over China based on three 21-yr simulations driven with boundary conditions from the ERA-Interim reanalysis data during 1989–2009. For each plant functional type (PFT), the plant pheonology, density, and fractional coverage in RegCM-CLM are all prescribed as static from year to year; RegCM-CLM-CN prescribes static fractional coverage but predicts plant phenology and density, and RegCM-CLM-CN-DV predicts plant phenology, density, and fractional coverage. Compared against the observational data, all three simulations reproduce the present-day climate well, including the wind fields, temperature and precipitation seasonal cycles, extremes, and interannual variabilities. Relative to RegCM-CLM, both RegCM-CLM-CN and RegCM-CLM-CN-DV perform better in simulating the interannual variability of temperature and spatial distribution of mean precipitation, but produce larger biases in the mean temperature field. RegCM-CLM-CN overestimates leaf area index (LAI), which enhances the cold biases and alleviates the dry biases found in RegCM-CLM. RegCM-CLM-CN-DV underestimates vegetation cover and/or stature, and hence overestimates surface albedo, which enhances the wintertime cold and dry biases found in RegM-CLM. During summer, RegCM-CLM-CN-DV overestimates LAI in south and east China, which enhances the cold biases through increased evaporative cooling; in the west where evaporation is low, the albedo effect of the underestimated vegetation cover is still dominant, leading to enhanced cold biases relative to RegCM-CLM.

Quantifying the indirect effects of nitrogen deposition on grassland litter chemical traits

Litter chemical traits are one of the dominant controls on litter decomposition. Increasing atmospheric nitrogen (N) deposition is expected to alter litter chemical traits at the community level in both direct (altering intraspecific chemistry) and indirect ways (changing species abundance and composition). Compared to intraspecific changes, the role of changes in species composition in driving the responses of litter chemical traits to N enrichment has been seldom quantitatively addressed. We quantified the relative contribution of intraspecific changes versus changes in community composition on litter traits and how this would be influenced by the magnitude of N deposition by taking advantage of a long-term field N addition experiment in a semi-arid grassland with a wide range of N addition rates. Nitrogen deposition altered plant species abundance by facilitating the dominance of one species with a nutrient acquisitive strategy, producing higher quality litter and being more responsive to N addition at the intraspecific level. Overall, changes in species composition, intraspecific changes and their interaction all led to higher litter quality (higher N and lower lignin, cellulose and hemicellulose concentrations) under N deposition treatments. The relative contribution of species composition on the responses of litter chemical traits to N deposition also increased with N addition rate, ranging from 5 to 40% for litter N, and from 2 to ~ 30% for the three structural carbon components. Our results demonstrate the positive impacts of increasing N deposition on litter quality through changing intraspecific C and N chemistry and species turnover, which has potential consequences for litter decomposition and nutrient cycling in ecosystems. Further, we highlight the important contribution of shifts in species abundance to the plant-mediated biogeochemical responses to N deposition.

Agreement between the Stages Cycling and PowerTap Powermeter

Several powermeters for almost every type of bicycle are available. The PowerTap (CycleOps) quantifies cycling power and cadence in the rear wheel hub and has already been validated in previous studies. The Stages Cycling Powermeter (Stages Cycling) is lower-priced and more flexible for usage as it measures in the left crank arm. The aim of this study was to determine the agreement between these two devices. 38 participants performed laboratory tests on a stationary roadbike. Power output and cadence were recorded with PowerTap and Stages simultaneously. Differences in power output and cadence were determined. The agreement between methods was quantified by use of mean differences and limits of agreement. Stages Powermeter underestimates power output by -1.9±4.0%) in comparison to the PowerTap (limits of agreement: 5.9% to -9.7%). Considering cadence, Stages calculates 0.94± 0.16) revolutions per minute more than the PowerTap (limits of agreement: -0.4 to 2.3 rpm). Mean coefficients of variation for power output (50.1%) and cadence (14.2%) estimate good reliability of Stages compared to PowerTap (50.3% and 14.3%). Despite a systematic bias, Stages can be considered a suitable alternative to measure power output. However, limitations regarding power output measurement have to be respected, especially when cycling with high intensities.