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AbstractTraditional approaches to monitoring road safety have primarily focused on measuring outcomes such as the number of fatalities and injuries. While effective in capturing overall trends, this macroscopic approach often overlooks the underlying causes of unsafe conditions. Recognizing these limitations, many countries now embrace a safe system-based approach, which emphasizes a holistic view of road safety, considering various elements and their interactions. In response to this shift, this study introduces a five-step framework designed to provide comprehensive coverage and tailored assistance in selecting and utilizing appropriate Road Safety Indicators (RSIs) for more effective performance monitoring. The framework integrates a novel RSIs taxonomy aligned with critical elements of the safe system. It also incorporates an MCDA-based approach to account for decision-makers’ preferences when selecting suitable RSIs. A case study demonstrates the practical application of the proposed steps, including the identification, classification, selection, and development of descriptive sheets for each selected RSI, as well as the continuous updating of the RSIs set. The findings offered valuable insights into the commonly used indicators in international road safety reports, while also revealing the limitations of currents metrics and data in fully capturing critical elements and hierarchical level within the road safety management system. [ABSTRACT FROM AUTHOR]

Error‐related negativity is a widely used measure of error monitoring, and many projects are independently moving ERN recorded during a flanker task toward standardization, optimization, and eventual clinical application. However, each project uses a different version of the flanker task and tacitly assumes ERN is functionally equivalent across each version. The routine neglect of a rigorous test of this assumption undermines efforts to integrate ERN findings across tasks, optimize and standardize ERN assessment, and widely apply ERN in clinical trials. The purpose of this registered report was to determine whether ERN shows similar experimental effects (correct vs. error trials) and data quality (intraindividual variability) during three commonly used versions of a flanker task. ERN was recorded from 172 participants during three versions of a flanker task across two study sites. ERN scores showed numerical differences between tasks, raising questions about the comparability of ERN findings across studies and tasks. Although ERN scores from all three versions of the flanker task yielded high data quality and internal consistency, one version did outperform the other two in terms of the size of experimental effects and the data quality. Exploratory analyses of the error positivity (Pe) provided tentative support for the other two versions of the task over the paradigm that appeared optimal for ERN. The present study provides a roadmap for how to statistically compare psychometric characteristics of ERP scores across paradigms and gives preliminary recommendations for flanker tasks to use for ERN‐ and Pe‐focused studies. Error‐related negativity (ERN) is assumed to be functionally equivalent across versions of the flanker. However, this assumption has not been rigorously tested. This registered report determined that one version outperformed the other two in terms of the size of the experimental effects and the data quality of ERN. This study provides a roadmap for how to statistically compare the psychometric characteristics of ERP scores across paradigms and gives preliminary recommendations for ERN studies. [ABSTRACT FROM AUTHOR]

Modern industrial control systems (ICSs), which consist of sensor nodes, actuators, and buses, contribute significantly to the enhancement of production efficiency. Massive node arrangements, security vulnerabilities, and complex operating status characterize ICSs, which lead to a threat to the industrial processes' stability. In this work, a condition-monitoring method for ICSs based on canonical variate analysis with probabilistic principal component analysis is proposed. This method considers the essential information of the operating data. Firstly, the one-way analysis of variance method is utilized to select the major variables that affect the operating performance. Then, a concurrent monitoring model based on probabilistic principal component analysis is established on both the serially correlated canonical subspace and its residual subspace, which is divided by canonical variate analysis. After that, monitoring statistics and control limits are constructed. Finally, the effectiveness and superiority of the proposed method are validated through comparisons with actual drilling operations. The method has better sensitivity than traditional monitoring methods. The experimental result reveals that the proposed method can effectively monitor the operating performance in a drilling process with its highest accuracy of 92.31% and a minimum monitoring delay of 11 s. The proposed method achieves much better effectiveness through real-world process scenarios due to its distributed structural division and the characteristic canonical analysis conducted in this paper. [ABSTRACT FROM AUTHOR]

Purpose This study aimed to compare internal load (IL) and external load (EL) variables between blocks of a game-based Rugby Sevens training session. Methods A descriptive cross-sectional study design was employed. Twenty-eight professional athletes from the first division of the Brazilian national championship were monitored during a game-based training session, which consisted of varying durations of ball-in-play blocks. The training session comprised 4 blocks of 1 min, 2 blocks of 2 min, and 1 block of 3 min of ball-in-play, with 1-min intervals between blocks of the same duration and 2-min intervals between blocks of different durations. Results A reduction in EL was reported during longer bouts of ball-in-play. Specifically, a reduction was observed when comparing block 5 to block 1 ( p = 0.021) and when comparing block 7 with blocks 1, 2, 3, 4, and 6 for distance per min. For accelerations and decelerations, blocks 5, 6, and 7 showed lower values than block 1 ( p = 0.001 and p = 0.005, respectively). Block 4 showed an increase in rate of perceived exertion (RPE) values compared to blocks 1 ( p = 0.010) and 2 ( p = 0.004). Increased RPE values were also found in block 5 compared to block 1 ( p = 0.001), as well as compared to blocks 2 ( p = 0.001) and 3 ( p = 0.002). RPE in block 7 was higher than in blocks 1, 2, 3, and 4 ( p = 0.001). Conclusions In summary, higher RPE values were reported across blocks, and IL appeared to be more volume-dependent.

The problem of monitoring the performance of technical systems is considered, corresponding to the stage of final control during the production of a product, as well as the stage of testing the product before its use. Based on the generalization and development of the existing approaches, models and methods for monitoring the performance of complex technical systems were developed, and models for predicting the parameters of their control were proposed. Methods of optimizing the number of tests of units of technical systems when monitoring their performance were developed. Methods for estimating the optimal level of the total defect rate are proposed. The efficiency of the proposed approaches is illustrated using a specific numerical example. The methods and models presented in the article can be useful for engineering and technical workers of design bureaus, research institutes, research and production associations and enterprises in ensuring the reliability of products and technical systems.

Summary: With the rise of exascale systems and large, data‐centric workflows, the need to observe and analyze high performance computing (HPC) applications during their execution is becoming increasingly important. HPC applications are typically not designed with online monitoring in mind, therefore, the observability challenge lies in being able to access and analyze interesting events with low overhead while seamlessly integrating such capabilities into existing and new applications. We explore how our service‐based observation, monitoring, and analytics (SOMA) approach to collecting and aggregating both application‐specific diagnostic data and performance data addresses these needs. We present our SOMA framework and demonstrate its viability with LULESH, a hydrodynamics proxy application. Then we focus on Astaroth, a multi‐GPU library for stencil computations, highlighting the integration of the TAU and APEX performance tools and SOMA for application and performance data monitoring. [ABSTRACT FROM AUTHOR]

This review aimed to systematically identify and comprehensively review the role of the cerebellum in performance monitoring, focusing on learning from and on processing of external feedback in non-motor learning. While 1078 articles were screened for eligibility, ultimately 36 studies were included in which external feedback was delivered in cognitive tasks and which referenced the cerebellum. These included studies in patient populations with cerebellar damage and studies in healthy subjects applying neuroimaging. Learning performance in patients with different cerebellar diseases was heterogeneous, with only about half of all patients showing alterations. One patient study using EEG demonstrated that damage to the cerebellum was associated with altered neural processing of external feedback. Studies assessing brain activity with task-based fMRI or PET and one resting-state functional imaging study that investigated connectivity changes following feedback-based learning in healthy participants revealed involvement particularly of lateral and posterior cerebellar regions in processing of and learning from external feedback. Cerebellar involvement was found at different stages, e.g., during feedback anticipation and following the onset of the feedback stimuli, substantiating the cerebellum's relevance for different aspects of performance monitoring such as feedback prediction. Future research will need to further elucidate precisely how, where, and when the cerebellum modulates the prediction and processing of external feedback information, which cerebellar subregions are particularly relevant, and to what extent cerebellar diseases alter these processes. [ABSTRACT FROM AUTHOR]

Social information can be used to optimize decision‐making. However, the simultaneous presentation of multiple sources of advice can lead to a distinction bias in judging the validity of the information. While the involvement of event‐related potential (ERP) components in social information processing has been studied, how they are modulated by (mis)judging an advisor's information validity remains unknown. In two experiments participants performed a decision‐making task with highly accurate or inaccurate cues. Each experiment consisted of an initial, learning, and test phase. During the learning phase, three advice cues were simultaneously presented and the validity of them had to be assessed. The effect of different cue constellations on ERPs was investigated. In the subsequent test phase, the willingness to follow or oppose an advice cue was tested. Results demonstrated the distinction bias with participants over or underestimating the accuracy of the most uncertain cues. The P2 amplitude was significantly increased during cue presentation when advisors were in disagreement as compared to when all were in agreement, regardless of cue validity. Further, a larger P3 amplitude during outcome presentation was found when advisors were in disagreement and increased with more informative cues. As such, the most uncertain cues were related to the smallest P3 amplitude. The findings hint at the possible role of P3 in judging and learning the predictability of social cues. This study provides novel insights into the role of P2 and P3 components during the judgment of social information validity. When considering advice of others during decision making, we often overestimate or underestimate how accurate the advisors' opinions are. In two experiments, we found that two event‐related potentials, P2 and P3, are associated with misjudging social information. Whereas P2 is modulated when observing advisors who disagree, P3 is associated with how informative a cue is for making the correct decision. Altogether, we demonstrate the electrophysiological correlates of (mis)judging social information. [ABSTRACT FROM AUTHOR]

Background: Human performers often recruit environment-based assistance to acquire or process information, such as relying on a smartphone app, a search engine, or a conversational agent. To make informed choices between several of such extended cognitive strategies, performers need to monitor the performance of these options. Objective: In the present study, we investigated whether participants monitor an extended cognitive strategy's performance—here, speed—more closely during initial as compared to later encounters. Methods: In three experiments, 737 participants were asked to first observe speed differences between two competing cognitive strategies—here, two competing algorithms that can obtain answers to trivia questions—and eventually choose between both strategies based on the observations. Results: Participants were sensitive to subtle speed differences and selected strategies accordingly. Most remarkably, even when participants performed identically with both strategies across all encounters, the strategy with superior speed in the initial encounters was preferred. Worded differently, participants exhibited a technology-use primacy effect. Contrarily, evidence for a recency effect was weak at best. Conclusion: These results suggest that great care is required when performers are first acquainted with novel ways to acquire or process information. Superior initial performance has the potential to desensitize the performer for inferior later performance and thus prohibit optimal choice. Application: Awareness of primacy enables users and designers of extended cognitive strategies to actively remediate suboptimal behavior originating in early monitoring episodes. [ABSTRACT FROM AUTHOR]

With the discovery of event‐related potentials elicited by errors more than 30 years ago, a new avenue of research on performance monitoring, cognitive control, and decision making emerged. Since then, the field has developed and expanded fulminantly. After a brief overview on the EEG correlates of performance monitoring, this article reviews recent advancements based on single‐trial analyses using independent component analysis, multiple regression, and multivariate pattern classification. Given the close interconnection between performance monitoring and reinforcement learning, computational modeling and model‐based EEG analyses have made a particularly strong impact. The reviewed findings demonstrate that error‐ and feedback‐related EEG dynamics represent variables reflecting how performance‐monitoring signals are weighted and transformed into an adaptation signal that guides future decisions and actions. The model‐based single‐trial analysis approach goes far beyond conventional peak‐and‐trough analyses of event‐related potentials and enables testing mechanistic theories of performance monitoring, cognitive control, and decision making. Performance monitoring and subsequent adaptations are highly dynamic processes. Here, I review recent advances in single‐trial EEG dynamics analyses that enabled the rigorous testing of predictions based on current theories and mathematically formalized computational models of performance monitoring, cognitive control, and decision making. I show that performance monitoring signals reflecting the transformation of outcome variables to adaptation signals are multiplexed in the EEG. [ABSTRACT FROM AUTHOR]

Purpose. This study aimed to compare internal load (IL) and external load (EL) variables between blocks of a game-based Rugby Sevens training session. Methods. A descriptive cross-sectional study design was employed. Twenty-eight professional athletes from the first division of the Brazilian national championship were monitored during a game-based training session, which consisted of varying durations of ball-in-play blocks. The training session comprised 4 blocks of 1 min, 2 blocks of 2 min, and 1 block of 3 min of ball-in-play, with 1-min intervals between blocks of the same duration and 2-min intervals between blocks of different durations. Results. A reduction in EL was reported during longer bouts of ball-in-play. Specifically, a reduction was observed when comparing block 5 to block 1 (p = 0.021) and when comparing block 7 with blocks 1, 2, 3, 4, and 6 for distance per min. For accelerations and decelerations, blocks 5, 6, and 7 showed lower values than block 1 (p = 0.001 and p = 0.005, respectively). Block 4 showed an increase in rate of perceived exertion (RPE) values compared to blocks 1 (p = 0.010) and 2 (p = 0.004). Increased RPE values were also found in block 5 compared to block 1 (p = 0.001), as well as compared to blocks 2 (p = 0.001) and 3 (p = 0.002). RPE in block 7 was higher than in blocks 1, 2, 3, and 4 (p = 0.001). Conclusions. In summary, higher RPE values were reported across blocks, and IL appeared to be more volume-dependent. [ABSTRACT FROM AUTHOR]

The error-related negativity (ERN) is a negative deflection in the electroencephalography (EEG) waveform at frontal-central scalp sites that occurs after error commission. The relationship between the ERN and broader patterns of brain activity measured across the entire scalp that support error processing during early childhood is unclear. We examined the relationship between the ERN and EEG microstates – whole-brain patterns of dynamically evolving scalp potential topographies that reflect periods of synchronized neural activity – during both a go/no-go task and resting-state in 90, 4-8-year-old children. The mean amplitude of the ERN was quantified during the -64 to 108 millisecond (ms) period of time relative to error commission, which was determined by data-driven microstate segmentation of error-related activity. We found that greater magnitude of the ERN associated with greater global explained variance (GEV; i.e., the percentage of total variance in the data explained by a given microstate) of an error-related microstate observed during the same -64 to 108 ms period (i.e., error-related microstate 3), and to greater anxiety risk as measured by parent-reported behavioral inhibition. During resting-state, six data-driven microstates were identified. Both greater magnitude of the ERN and greater GEV values of error-related microstate 3 associated with greater GEV values of resting-state microstate 4, which showed a frontal-central scalp topography. Source localization results revealed overlap between the underlying neural generators of error-related microstate 3 and resting-state microstate 4 and canonical brain networks (e.g., ventral attention) known to support the higher-order cognitive processes involved in error processing. Taken together, our results clarify how individual differences in error-related and intrinsic brain activity are related and enhance our understanding of developing brain network function and organization supporting error processing during early childhood. [ABSTRACT FROM AUTHOR]

Disorders marked by high levels of impulsivity and compulsivity have been linked to changes in performance monitoring, specifically the error‐related negativity (ERN). We investigated the relationship between performance monitoring and individual differences in impulsivity and compulsivity. A total of 142 participants were recruited into four groups, each with different combinations of impulsivity and compulsivity, and they performed a flanker task to assess error‐related brain activity. We defined error‐related brain activity as ERN amplitude and theta power. Single‐trial regression was employed to analyze the amplitude differences between incorrect and correct trials within the ERN time window. The findings revealed that impulsivity, compulsivity, and different measures of response processing exhibited distinct interactions, which were influenced by the configuration of impulsivity and compulsivity, but also depended on the measure of response processing. Specifically, high compulsivity predicted larger ERN amplitudes in individuals with low impulsivity, whereas high impulsivity had no significant effect on ERN amplitude in individuals with low compulsivity. Furthermore, when both impulsivity and compulsivity were high, no significant increase in ERN amplitude was observed; instead, there was a reduced difference between incorrect and correct trials. No significant differences were found for theta power. While the association between error‐related brain activity and transdiagnostic markers or psychopathology may be smaller than generally assumed, considering the interaction between different transdiagnostic markers and their facets can enhance our understanding of the complex associations that arise during the investigation of neural correlates of performance monitoring, specifically the ERN. Our findings emphasize the importance of investigating interactions between transdiagnostic markers like impulsivity and compulsivity: the error‐related negativity (ERN) was elevated for high compulsivity only when impulsivity was low, complementing previous research on the ERN in compulsivity. When both impulsivity and compulsivity were high, we observed no elevation in ERN amplitude but a reduced difference between ERN and correct‐response negativity. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of monitoring intensity on individuals' motivation to exert effort. Using an experimental approach, we designed a test comprising six problems, with varied levels of monitoring and success criteria, to evaluate performance as an indicator of effort. The results reveal a nonlinear relationship between the stringency of monitoring criteria and worker performance. Interestingly, we found that optimal performance is attained when participants are required to answer correctly only one of the six problems. This study enhances our understanding of performance monitoring strategies and their effects in modern work settings. [ABSTRACT FROM AUTHOR]

Abstract It has been demonstrated that during motor responses, the activation of the motor cortical regions emerges in close association with the activation of the medial frontal cortex implicated with performance monitoring and cognitive control. The present study explored the oscillatory neurodynamics of response-related potentials during correct and error responses to test the hypothesis that such continuous communication would modify the characteristics of motor potentials during performance errors. Electroencephalogram (EEG) was recorded at 64 electrodes in a four-choice reaction task and response-related potentials (RRPs) of correct and error responses were analysed. Oscillatory RRP components at extended motor areas were analysed in the theta (3.5–7 Hz) and delta (1–3 Hz) frequency bands with respect to power, temporal synchronization (phase-locking factor, PLF), and spatial synchronization (phase-locking value, PLV). Major results demonstrated that motor oscillations differed between correct and error responses. Error-related changes (1) were frequency-specific, engaging delta and theta frequency bands, (2) emerged already before response production, and (3) had specific regional topographies at posterior sensorimotor and anterior (premotor and medial frontal) areas. Specifically, the connectedness of motor and sensorimotor areas contra-lateral to the response supported by delta networks was substantially reduced during errors. Also, there was an error-related suppression of the phase stability of delta and theta oscillations at these areas. This synchronization reduction was accompanied by increased temporal synchronization of motor theta oscillations at bi-lateral premotor regions and by two distinctive error-related effects at medial frontal regions: (1) a focused fronto-central enhancement of theta power and (2) a separable enhancement of the temporal synchronization of delta oscillations with a localized medial frontal focus. Together, these observations indicate that the electrophysiological signatures of performance errors are not limited to the medial frontal signals, but they also involve the dynamics of oscillatory motor networks at extended cortical regions generating the movement. Also, they provide a more detailed picture of the medial frontal processes activated in relation to error processing.

Based on previous concepts that a distributed theta network with a central "hub" in the medial frontal cortex is critically involved in movement regulation, monitoring, and control, the present study explored the involvement of this network in error processing with advancing age in humans. For that aim, the oscillatory neurodynamics of motor theta oscillations was analyzed at multiple cortical regions during correct and error responses in a sample of older adults. Response-related potentials (RRPs) of correct and incorrect reactions were recorded in a four-choice reaction task. RRPs were decomposed in the time-frequency domain to extract oscillatory theta activity. Motor theta oscillations at extended motor regions were analyzed with respect to power, temporal synchronization, and functional connectivity. Major results demonstrated that errors had pronounced effects on motor theta oscillations at cortical regions beyond the medial frontal cortex by being associated with (1) theta power increase in the hemisphere contra-lateral to the movement, (2) suppressed spatial and temporal synchronization at pre-motor areas contra-lateral to the responding hand, (2) inhibited connections between the medial frontal cortex and sensorimotor areas, and (3) suppressed connectivity and temporal phase-synchronization of motor theta networks in the posterior left hemisphere, irrespective of the hand, left, or right, with which the error was made. The distributed effects of errors on motor theta oscillations demonstrate that theta networks support performance monitoring. The reorganization of these networks with aging implies that in older individuals, performance monitoring is associated with a disengagement of the medial frontal region and difficulties in controlling the focus of motor attention and response selection. [ABSTRACT FROM AUTHOR]

It has been demonstrated that during motor responses, the activation of the motor cortical regions emerges in close association with the activation of the medial frontal cortex implicated with performance monitoring and cognitive control. The present study explored the oscillatory neurodynamics of response-related potentials during correct and error responses to test the hypothesis that such continuous communication would modify the characteristics of motor potentials during performance errors. Electroencephalogram (EEG) was recorded at 64 electrodes in a four-choice reaction task and response-related potentials (RRPs) of correct and error responses were analysed. Oscillatory RRP components at extended motor areas were analysed in the theta (3.5–7 Hz) and delta (1–3 Hz) frequency bands with respect to power, temporal synchronization (phase-locking factor, PLF), and spatial synchronization (phase-locking value, PLV). Major results demonstrated that motor oscillations differed between correct and error responses. Error-related changes (1) were frequency-specific, engaging delta and theta frequency bands, (2) emerged already before response production, and (3) had specific regional topographies at posterior sensorimotor and anterior (premotor and medial frontal) areas. Specifically, the connectedness of motor and sensorimotor areas contra-lateral to the response supported by delta networks was substantially reduced during errors. Also, there was an error-related suppression of the phase stability of delta and theta oscillations at these areas. This synchronization reduction was accompanied by increased temporal synchronization of motor theta oscillations at bi-lateral premotor regions and by two distinctive error-related effects at medial frontal regions: (1) a focused fronto-central enhancement of theta power and (2) a separable enhancement of the temporal synchronization of delta oscillations with a localized medial frontal focus. Together, these observations indicate that the electrophysiological signatures of performance errors are not limited to the medial frontal signals, but they also involve the dynamics of oscillatory motor networks at extended cortical regions generating the movement. Also, they provide a more detailed picture of the medial frontal processes activated in relation to error processing. [ABSTRACT FROM AUTHOR]

Aero-engines are highly complex machines, and their reliability and lifespan directly impact flight safety. As a result, aero-engine reliability has become a significant research field. This paper aims to comprehensively summarize the progress in aero-engine reliability research. First, we analyzed the existing structures of aircraft engines, as well as the current research on reliability and commonly used estimation methods. Second, we reviewed the techniques employed for monitoring operational status and diagnosing faults in aircraft engines. Third, we summarized the optimization methods frequently used in fault diagnosis and lifespan prediction. Fourth, we conducted a bibliometric analysis. Finally, we identified potential challenges for future research. Based on our literature review, we found that: 1) mathematical modeling-based and data-driven approaches are currently the most commonly used methods for performance monitoring; 2) neural networks and deep learning are the most popular methods for fault diagnosis and lifespan prediction; 3) the bibliometric analysis reveals that China’s interest in aero-engine reliability research techniques is higher than that of other countries; and 4) further development is needed in the areas of overall system reliability, real-world usage scenario studies, and advanced simulation and modeling.

In this paper, we present a methodology, by utilising a nonparametric multivariate cumulative sum control chart and data envelopment analysis in tandem, to evaluate and monitor distribution network performance by simultaneously considering multiple performance factors and their interrelationships. While these methods were previously applied individually, we demonstrate that their combined use can provide more powerful results in performance assessment, monitoring and improvement. Our approach contributes to the domain of supply chain analytics and risk management as it can provide new insights into network performance based on real time and past data. We present the application of our approach on data obtained from The Dow Chemical Company. [ABSTRACT FROM AUTHOR]

Prenatal opioid exposure is one consequence of the opioid epidemic, but effects on child development remain poorly understood. There is emerging evidence that children exposed to opioids in utero exhibit elevated emotional and behavioral problems, which may be partially due to alterations in cognitive control. Using multiple methods (i.e., neuropsychological, behavioral, and event-related potential [ERP] assessments), the present study examined differences in emotional, behavioral, and cognitive control difficulties in preschool-aged children with (n = 21) and without (n = 23) prenatal opioid exposure (Mage = 4.30, SD = 0.77 years). Child emotional and behavioral problems were measured with a caregiver questionnaire, indicators of cognitive control were measured using developmentally appropriate behavioral (i.e., delay discounting, Go/No-Go) and neuropsychological (i.e., Statue) tasks, and electroencephalogram was recorded to error and correct responses in a Go/No-Go task. ERP analyses focused on the error-related negativity (ERN), an ERP that reflects error monitoring, and correct-response negativity (CRN), a component reflecting performance monitoring more generally. Opioid exposure was associated with elevated difficulties across domains and a blunted ERN, reflecting altered cognitive control at the neural level, but groups did not significantly differ on behavioral measures of cognitive control. These result replicate prior studies indicating an association between prenatal opioid exposure and behavioral problems in preschool-aged children. Further, our findings suggest these differences may be partially due to children with prenatal opioid exposure exhibiting difficulties with cognitive control at the neural level. The ERN is a potential target for future research and intervention efforts to address the sequelae of prenatal opioid exposure. [ABSTRACT FROM AUTHOR]

New and promising variables are being developed to analyze performance and fatigue in trail running, such as mechanical power, metabolic power, metabolic cost of transport and mechanical efficiency. The aim of this study was to analyze the behavior of these variables during a real vertical kilometer field test. Fifteen trained trail runners, eleven men (from 22 to 38 years old) and four women (from 19 to 35 years old) performed a vertical kilometer with a length of 4.64 km and 835 m positive slope. During the entire race, the runners were equipped with portable gas analyzers (Cosmed K5) to assess their cardiorespiratory and metabolic responses breath by breath. Significant differences were found between top-level runners versus low-level runners in the mean values of the variables of mechanical power, metabolic power and velocity. A repeated-measures ANOVA showed significant differences between the sections, the incline and the interactions between all the analyzed variables, in addition to differences depending on the level of the runner. The variable of mechanical power can be statistically significantly predicted from metabolic power and vertical net metabolic COT. An algebraic expression was obtained to calculate the value of metabolic power. Integrating the variables of mechanical power, vertical velocity and metabolic power into phone apps and smartwatches is a new opportunity to improve performance monitoring in trail running. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to evaluate the learning curve of thoracoscopic repair of tracheoesophageal fistula (TEF) by a single surgeon using a cumulative sum (CUSUM) analysis. Methods: Prospective clinical data of consecutive Gross type-C TEF repairs performed by a pediatric surgeon from 2010 to 2020 were recorded. CUSUM charts for anastomosis and operating times were generated. The learning curves were compared with the effect of accumulation based on case experience. Results: For 33 consecutive cases, the mean operative and anastomosis times were 139 ± 39 min and 3137 ± 1110 s, respectively. Significant transitions beyond the learning phase for total operating and anastomosis times were observed at cases 13 and 17. Both the total operating time and anastomosis time were significantly faster in the proficiency improvement phase than in the initial learning phase. Postoperative complications significantly decreased after the initial anastomosis learning phase but not after the initial total operating learning phase. Conclusions: Thoracoscopic repair of TEF is considered safe and feasible after 13 cases, where the surgeon can improve their proficiency with the total operation procedure, and 17 cases, which will enable the surgeon to achieve proficiency in anastomosis. Postoperative complications significantly decreased after gaining familiarity with the anastomosis procedure through the learning phase. [ABSTRACT FROM AUTHOR]

Introduction: Numerous studies have found that expert players anticipate better than novices. If more accurate prediction represents performance monitoring of experts, what are the advantages of elite basketball players in identifying and processing available cues? There is still a lack of sufficient evidence. This study examined the visual search in basketball players and explored the performance monitoring of action anticipation, adopting an expert–novice paradigm and eye‐movement technology. Methods: Forty basketball players were recruited in this study: 20 in the expert group and 20 in the novice group. Participants were asked to predict the outcome of videotaped basketball throws and their accuracy and eye‐movement characteristics were record. Results: The accuracy of the expert was significantly higher than that of the novice. The experts were able to instantly search and identify important cues in anticipation, and the gaze area of the experts was concentrated on the area of interest of the body. Additionally, the expert group showed long, repetitive, and rapid visual search of vital information, and improved their performance of the task. Conclusion: The experts could monitor the performance of prediction by grabbing vital shooting information (such as the body of a player). The results suggest the athletes and coaches that if they want to improve the ability of prediction, it may be useful to shift their focus of attention from ball trajectory to body action. [ABSTRACT FROM AUTHOR]

Given that people currently live in a digital age, and swimming is an internationally known sport, this paper aims to identify, analyze and compare several electronic devices built to monitor the performance of athletes who are involved in this type of competitions. [ABSTRACT FROM AUTHOR]

While often seeming to investigate rather different problems, research into value-based decision making and cognitive control have historically offered parallel insights into how people select thoughts and actions. While the former studies how people weigh costs and benefits to make a decision, the latter studies how they adjust information processing to achieve their goals. Recent work has highlighted ways in which decision-making research can inform our understanding of cognitive control. Here, we provide the complementary perspective: how cognitive control research has informed understanding of decision-making. We highlight three particular areas of research where this critical interchange has occurred: (1) how different types of goals shape the evaluation of choice options, (2) how people use control to adjust the ways they make their decisions, and (3) how people monitor decisions to inform adjustments to control at multiple levels and timescales. We show how adopting this alternate viewpoint offers new insight into the determinants of both decisions and control; provides alternative interpretations for common neuroeconomic findings; and generates fruitful directions for future research.

Abstract Introduction Numerous studies have found that expert players anticipate better than novices. If more accurate prediction represents performance monitoring of experts, what are the advantages of elite basketball players in identifying and processing available cues? There is still a lack of sufficient evidence. This study examined the visual search in basketball players and explored the performance monitoring of action anticipation, adopting an expert–novice paradigm and eye‐movement technology. Methods Forty basketball players were recruited in this study: 20 in the expert group and 20 in the novice group. Participants were asked to predict the outcome of videotaped basketball throws and their accuracy and eye‐movement characteristics were record. Results The accuracy of the expert was significantly higher than that of the novice. The experts were able to instantly search and identify important cues in anticipation, and the gaze area of the experts was concentrated on the area of interest of the body. Additionally, the expert group showed long, repetitive, and rapid visual search of vital information, and improved their performance of the task. Conclusion The experts could monitor the performance of prediction by grabbing vital shooting information (such as the body of a player). The results suggest the athletes and coaches that if they want to improve the ability of prediction, it may be useful to shift their focus of attention from ball trajectory to body action.

Procrastination is an irrational delay of task completion. Previous studies have demonstrated that individuals who often procrastinate present deficits in attentional control and performance monitoring and that these dysfunctions might be differentially manifested depending on the motivational context. Building upon these results, the present event-related potential (ERP) study aimed to investigate the impact of norm-referenced feedback on executive functions among students with high (HP; N = 75) or low (LP; N = 77) procrastination levels. Participants completed the parametric Go/No-Go task, while receiving either positive or negative false feedback indicating how well they performed in comparison to others. The results indicated that positive (as opposed to negative) feedback led to higher self-reported arousal and increased post-error slowing in HP (vs. LP) participants. Moreover, neurophysiological measures indicated lower neural activation linked to attentional control (P300) and performance monitoring (ERN, CRN and Pe) in HP than LP participants, while the groups did not differ in these indices during the positive feedback condition. Obtained findings indicate that HP might be more sensitive to the motivating effects of success and more vulnerable to the detrimental influence of failure. • High (vs. low) procrastination was linked to higher arousal after positive evaluation. • High procrastination was linked to lower brain activity after negative evaluation. • Norm-referenced feedback might impact procrastination-related cognitive dysfunctions. [ABSTRACT FROM AUTHOR]

The vertical jump height has been widely used in sports-related studies to track athletes' development. Although many systems can measure vertical jump height, there are still problems with measuring it in real-time during sports activity. Therefore, the use of inertial measurement unit (IMU)-based systems in this area is increasing. In this study, a low-cost, small, wireless, and wearable jump meter has been designed to address the real-time measurement problem. The developed system has a high accuracy for vertical jump measurements and provides some extra parameters for performance evaluation. Fourteen volleyball players' measurements were taken simultaneously with the designed system and a jump mat to evaluate the developed system's performance (n = 350). The obtained results show that the system is highly correlated with jump mat (r2 = 0.92), and it also has a mean bias of −0.06 cm (95% limits of agreement −3.4 cm to 3.3 cm; p < 0.001). [ABSTRACT FROM AUTHOR]

Purpose: In climbing, exceptional levels of fingertip strength across different holds and body positions are considered essential for performance. There is no commonly agreed upon way to measure such "grip strength variability." Furthermore, the accurate and reliable monitoring of strength is necessary to achieve safe, progressive improvement in strength. Therefore, this study aimed to develop reliability and criterion validity for assessment of grip strength across multiple holds and body positions. Methods: Twenty-two advanced toelite climbers (age = 28.5 ± 8.6 years) performed maximal voluntary isometric contractions on two occasions (for test-retest reliability). Conditions included two hold types (edge and sloper) tested in two postures (elbow flexion [90°] and self-preferred). Climbing performance was determined on two "difficulty" routes (difficulty increases with each hold): one route composed of only edges and another only of slopers. Results: Test-retest reliability was high (ICC between 0.94–0.99). Significant positive correlations were observed for the forces produced on the sloper test and climbing distance on the sloper route (r = 0.512,p <.05), and for the forces produced on the edge test and climbing distance on the edge route (ρ = 0.579, p <.01). Conclusion: These findings support reliability and validity of the method used to measure grip strength variability with different holds and body positions and suggest that improving strength across different grasping types supports adaptive climbing performance. [ABSTRACT FROM AUTHOR]

Background and Purpose: Clinical Artificial Intelligence (AI) implementations lack ground-truth when applied on real-world data. This study investigated how combined geometrical and dose-volume metrics can be used as performance monitoring tools to detect clinically relevant candidates for model retraining. Materials and Methods: Fifty patients were analyzed for both AI-segmentation and planning. For AI-segmentation, geometrical (Standard Surface Dice 3 mm and Local Surface Dice 3 mm) and dose-volume based parameters were calculated for two organs (bladder and anorectum) to compare AI output against the clinically corrected structure. A Local Surface Dice was introduced to detect geometrical changes in the vicinity of the target volumes, while an Absolute Dose Difference (ADD) evaluation increased focus on dose-volume related changes. AI-planning performance was evaluated using clinical goal analysis in combination with volume and target overlap metrics. Results: The Local Surface Dice reported equal or lower values compared to the Standard Surface Dice (anorectum: (0.93 ± 0.11) vs (0.98 ± 0.04); bladder: (0.97 ± 0.06) vs (0.98 ± 0.04)). The ADD metric showed a difference of (0.9 ± 0.8)Gy for the anorectum D1cm3. The bladder D5cm3 reported a difference of (0.7 ± 1.5)Gy. Mandatory clinical goals were fulfilled in 90 % of the DLP plans. Conclusions: Combining dose-volume and geometrical metrics allowed detection of clinically relevant changes, applied to both auto-segmentation and auto-planning output and the Local Surface Dice was more sensitive to local changes compared to the Standard Surface Dice. This monitoring is able to evaluate AI behavior in clinical practice and allows candidate selection for active learning.

Performance monitoring is essential for successful action execution and previous studies have suggested that frontomedial theta (FMT) activity in scalp-recorded EEG reflects need for control signaling in response to negative outcomes. However, these studies have overlooked the fact that anticipating the most probable outcome is often possible. To optimize action execution, it is necessary for the time-critical performance monitoring system to utilize continuously updated information to adjust actions in time. This study used a combination of mobile EEG and virtual reality to investigate how the performance monitoring system adapts to continuously updated information during brief phases of outcome evaluation that follow action execution. In two virtual shooting tasks, participants were either able to observe the projectile and hence anticipate the outcome or not. We found that FMT power increased in response to missing shots in both tasks, but this effect was suppressed when participants were able to anticipate the outcome. Specifically, the suppression was linearly related to the duration of the anticipatory phase. Our results suggest that the performance monitoring system dynamically integrates incoming information to evaluate the most likely outcome of an action as quickly as possible. This dynamic mode of performance monitoring provides significant advantages over idly waiting for an action outcome before getting engaged. Early and adaptive performance monitoring not only helps prevent negative outcomes but also improves overall performance. Our findings highlight the crucial role of dynamic integration of incoming information in the performance monitoring system, providing insights for real-time decision-making and action control.

Overall caecum intubation rate(oCIR) and overall polyp detection rate(oPDR) have been proposed as performance indicators, but varying complexity in case mix among endoscopists may potentially affect validity. The study aims to explore the effect of adjusting for case mix on individual endoscopist performance by calculating case mix-adjusted performance estimates (cmCIR and cmPDR) and comparing them to overall performance estimates (oCIR and oPDR). The study also provides an R program for case mix analysis. Logistic regression associated endoscopist, colonoscopy indication, patient age and patient gender with the binary outcomes of cecum intubation and polyp detection. Case mix-adjusted performance indicators were calculated for each endoscopist based on logistic regression and bootstraps. Endoscopists were ranked from best to worst by overall and case mix-adjusted performance estimates, and differences were evaluated using percentage points(pp) and rank changes. The dataset consisted of 7376 colonoscopies performed by 47 endoscopists. The maximum rank change for an endoscopist comparing oCIR and cmCIR was eight positions, interquartile range (IQR 1–3). The maximum change in CIR was 1.95 percentage point (pp) (IQR 0.27–0.86). The maximum rank change in the oPDR versus cmPDR analysis was 17 positions (IQR 1.5–8.5). The maximum change in PDR was 11.21 pp (IQR 2.05–6.70). Three endoscopists improved their performance from significantly inferior to within the 95% confidence interval (CI) range of performance targets using case mix-adjusted estimates. The majority of endoscopists were unaffected by adjustment for case mix, but a few unfortunate endoscopists had an unfavourable case mix that could invite incorrect suspicion of inferior performance. [ABSTRACT FROM AUTHOR]

Background: Difficulty in cognitive adjustment after a conflict or error is a hallmark for many psychiatric disorders, yet the underlying neural correlates are not fully understood. We have previously shown that post-success and post-error cognitive controls are associated with distinct mechanisms particularly related to the prefrontal-cerebellar circuit, raising the possibility that altered dynamic interactions in this circuit may underlie mental illness. Methods: This study included 136 patients with three diagnosed disorders [48 schizophrenia (SZ), 49 bipolar disorder (BD), 39 attention deficit hyperactivity disorder (ADHD)] and 89 healthy controls who completed a stop-signal task during fMRI scans. Brain activations for concurrent, post-success, and post-error cognitive controls were analyzed and compared between groups. Dynamic causal modeling was applied to investigate prefrontal-cerebellar effective connectivity patterns during post-success and post-error processing. Results: No significant group differences were observed for brain activations and overall effective connectivity structures during post-success and post-error conditions. However, significant group differences were shown for the modulational effect on top-down connectivity from the prefrontal cortex to the cerebellum during post-error trials (pFWE = 0.02), which was driven by reduced modulations in both SZ and ADHD. During post-success trials, there were significantly decreased modulational effect on bottom-up connectivity from the cerebellum to the prefrontal cortex in ADHD (pFWE = 0.04) and decreased driving input to the cerebellum in SZ (pFWE = 0.04). Conclusions: These findings suggest that patients with SZ and ADHD are associated with insufficient neural modulation on the prefrontal-cerebellar circuit during post-success and post-error cognitive processing, a phenomenon that may underlie cognitive deficits in these disorders. [ABSTRACT FROM AUTHOR]