Cost Of Effort Research Articles

Robust Prediction of Relative Binding Energies for Protein–Protein Complex Mutations Using Free Energy Perturbation Calculations

Computational free energy-based methods have the potential to significantly improve throughput and decrease costs of protein design efforts. Such methods must reach a high level of reliability, accuracy, and automation to be effectively deployed in practical industrial settings in a way that impacts protein design projects. Here, we present a benchmark study for the calculation of relative changes in protein–protein binding affinity for single point mutations across a variety of systems from the literature, using free energy perturbation (FEP+) calculations. We describe a method for robust treatment of alternate protonation states for titratable amino acids, which yields improved correlation with and reduced error compared to experimental binding free energies. Following careful analysis of the largest outlier cases in our dataset, we assess limitations of the default FEP+ protocols and introduce an automated script which identifies probable outlier cases that may require additional scrutiny and calculates an empirical correction for a subset of charge-related outliers. Through a series of three additional case study systems, we discuss how Protein FEP+ can be applied to real-world protein design projects, and suggest areas of further study.

Growth trajectories and roles of expectancy, task value, and cost in middle-school physical education

This longitudinal investigation tracked the progression of students’ expectancy for success, task value, and perceived cost in the context of physical education throughout an academic year. The study involved 399 middle-school students from China, and data were collected at three distinct time points. Analysis using latent growth curve models revealed positive trajectories in both expectancy and task value, along with decreases in perceived cost. Variations in motivation were observed based on demographic factors, both in initial motivation levels and change rate. At the beginning of the academic year, senior students, girls, and students who were overweight exhibited lower motivation compared to their counterparts, but these motivation disparities tended to reduce over time. Changes in motivation were significant predictors of learning outcomes. Students who sustained high levels of expectancy and task value while reducing their perceived effort cost demonstrated higher cardiorespiratory fitness. The findings expand the theoretical understanding of expectancy, task value, and cost, thereby supporting the feasibility of implementing programmatic interventions to bolster motivation in physical education.

“I just don’t find it interesting”: academic major and timing of enrollment predict motivation in an introductory biology course

ABSTRACT Situated expectancy-value theory (SEVT) posits that students’ expectancies for success, task values, and perceived costs affect their performance in STEM courses. Less is known about how students’ majors and timing of course completion affect motivational processes. Using the SEVT framework, this study utilised a convergent mixed methods approach to investigate academic motivation among students (N = 646) who enrolled in introductory biology at a large public university. Survey data revealed that students majoring in Biology were more motivated than students from other majors, although academic major was not directly associated with final grade. Upper-level students reported significantly lower competence-related beliefs and task values and perceived higher effort cost compared to first-year students. Upper-level students also earned significantly lower grades than first-year students. Both academic major and year in college had significant indirect effects on final course grades. Interviews with students (N = 31) helped explain and extend quantitative results. This study demonstrates that understudied factors (i.e. academic major and year in college) are important predictors of motivation in a gateway biology course and identifies themes that contribute to student motivation in this context.

Male allocation to ejaculation and mating effort imposes different life history trade-offs.

When males compete, sexual selection favors reproductive traits that increase their mating or fertilization success (pre- and postcopulatory sexual selection). It is assumed that males face a trade-off between these 2 types of sexual traits because they both draw from the same pool of resources. Consequently, allocation into mate acquisition or ejaculation should create similar trade-offs with other key life history traits. Tests of these assumptions are exceedingly rare. Males only ejaculate after they mate, and the costs of ejaculation are therefore highly confounded with those of mating effort. Consequently, little is known about how each component of reproductive allocation affects a male's future performance. Here, we ran an experiment using a novel technique to distinguish the life history costs of mating effort and ejaculation for mosquitofish (Gambusia holbrooki). We compared manipulated males (mate without ejaculation), control males (mate and ejaculate), and naïve males (neither mate nor ejaculate) continuously housed with a female and 2 rival males. We assessed their growth, somatic maintenance, mating and fighting behavior, and sperm traits after 8 and 16 weeks. Past mating effort significantly lowered a male's future mating effort and growth, but not his sperm production, while past sperm release significantly lowered a male's future ejaculate quantity, but not his mating effort. Immune response was the only trait impacted by both past mating effort and past ejaculation. These findings challenge the assumption that male reproductive allocation draws from a common pool of resources to generate similar life history costs later in life. Instead, we provide clear evidence that allocation into traits under pre- and postcopulatory sexual selection have different trait-specific effects on subsequent male reproductive performance.

Productive scientists are associated with lower disruption in scientific publishing

While scientific researchers often aim for high productivity, prioritizing the quantity of publications may come at the cost of time and effort dedicated to individual research. It is thus important to examine the relationship between productivity and disruption for individual researchers. Here, we show that with the increase in the number of published papers, the average citation per paper will be higher yet the mean disruption of papers will be lower. In addition, we find that the disruption of scientists' papers may decrease when they are highly productive in a given year. The disruption of papers in each year is not determined by the total number of papers published in the author's career, but rather by the productivity of that particular year. Besides, more productive authors also tend to give references to recent and high-impact research. Our findings highlight the potential risks of pursuing productivity and aim to encourage more thoughtful career planning among scientists.

Disentangling effort from probability of success: Temporal dynamics of frontal midline theta in effort-based reward processing

The ability to weigh a reward against the effort required to acquire it is critical for decision-making. However, extant experimental paradigms oftentimes confound increased effort demand with decreased reward probability, thereby obscuring neural correlates underlying these cognitive processes. To resolve this issue, we designed novel tasks that disentangled probability of success – and therefore reward probability – from effort demand. In Experiment 1, reward magnitude and effort demand were varied while reward probability was kept constant. In Experiment 2, effort demand and reward probability were varied while reward magnitude remained fixed. Electroencephalogram (EEG) data was recorded to explore how frontal midline theta (FMT; an electrophysiological index of mPFC function) and component P3 (an index of incentive salience) respond to effort demand, and reward magnitude and probability. We found no evidence that FMT tracked effort demands or net value during cue evaluation. At feedback, however, FMT power was enhanced for high compared to low effort trials, but not modulated by reward magnitude or probability. Conversely, P3 was sensitive to reward magnitude and probability at both cue and feedback phases and only integrated expended effort costs at feedback, such that P3 amplitudes continued to scale with reward magnitude and probability but were also increased for high compared to low effort reward feedback. These findings suggest that, when likelihood of success is equal, FMT power does not track net value of prospective effort-based rewards. Instead, expended cognitive effort potentiates FMT power and enhances the saliency of rewards at feedback. Significance statementThe way the brain weighs rewards against the effort required to achieve them is critical for understanding motivational disorders. Current paradigms confound increased effort demand with decreased reward probability, making it difficult to disentangle neural activity associated with effort costs from those associated with reward likelihood. Here, we explored the temporal dynamics of effort-based reward (via frontal midline theta (FMT) and component P3) while participants underwent a novel paradigm that kept probability of reward constant between mental effort demand conditions. Our findings suggest that the FMT does not track net value and that expended effort enhances, instead of attenuates, the saliency of rewards.

Wagers for work: Decomposing the costs of cognitive effort.

Some aspects of cognition are more taxing than others. Accordingly, many people will avoid cognitively demanding tasks in favor of simpler alternatives. Which components of these tasks are costly, and how much, remains unknown. Here, we use a novel task design in which subjects request wages for completing cognitive tasks and a computational modeling procedure that decomposes their wages into the costs driving them. Using working memory as a test case, our approach revealed that gating new information into memory and protecting against interference are costly. Critically, other factors, like memory load, appeared less costly. Other key factors which may drive effort costs, such as error avoidance, had minimal influence on wage requests. Our approach is sensitive to individual differences, and could be used in psychiatric populations to understand the true underlying nature of apparent cognitive deficits.

An analysis of precautionary behavior in retirement decision making with an application to pension system reform

We analyze how precautionary motives affect the decisions of a risk-averse agent on saving, labor supply and retirement. In a setting where there is a random shock which affects agent disutility from work, we show that uncertainty directly affects retirement age and saving, but leaves labor supply during working age unchanged. In particular, a precautionary motive for retirement always arises, which pushes the agent to bring forward retirement in the presence of a risk on the cost of work effort. Moreover, prudence and a sufficiently high level of absolute temperance are sufficient conditions for precautionary saving. In this setting, we also study the effects of two common reforms of the pension system: an increase in pension contributions and a cut in pension benefits. The conditions for the agent to postpone retirement and increase labor supply are studied. This makes it possible to characterize the circumstances when the financial soundness of the pension system improves after these reforms.

Pre-crastination across physical and cognitive tasks.

Pre-crastination refers to the tendency to begin a task as soon as possible, even at the cost of additional effort. This phenomenon is consistently observed in tasks in which participants are asked to select one of two buckets to carry to a target. Surprisingly, on a high proportion of trials participants choose the bucket that is closer to them (and further from the target) as opposed to the bucket that is further from them (and closer to the target). In other words, participants tend to complete the task of picking up a bucket as soon as possible, even when this requires additional physical effort. The purpose of the current experiment was to test whether an individual's tendency to pre-crastinate is stable across tasks. Participants performed a physical load task where they selected one of two buckets to carry to a target. The same participants performed a cognitive load task where they picked up number strings at one of the two bucket locations and mentally carried the number string to a target. We found that participants pre-crastinated in both tasks and this tendency was reduced as task difficulty increased. Importantly, we found a significant association between an individual's tendency to pre-crastinate in the physical load task and their tendency to pre-crastinate in the cognitive load task. Thus, an individual's tendency to pre-crastinate is consistent across tasks and suggests that this is a stable characteristic of how individuals choose to order tasks.

Comparison of Metabolic Power and Energy Cost of Submaximal and Sprint Running Efforts Using Different Methods in Elite Youth Soccer Players: A Novel Energetic Approach.

Sprinting is a decisive action in soccer that is considerably taxing from a neuromuscular and energetic perspective. This study compared different calculation methods for the metabolic power (MP) and energy cost (EC) of sprinting using global positioning system (GPS) metrics and electromyography (EMG), with the aim of identifying potential differences in performance markers. Sixteen elite U17 male soccer players (age: 16.4 ± 0.5 years; body mass: 64.6 ± 4.4 kg; and height: 177.4 ± 4.3 cm) participated in the study and completed four different submaximal constant running efforts followed by sprinting actions while using portable GPS-IMU units and surface EMG. GPS-derived MP was determined based on GPS velocity, and the EMG-MP and EC were calculated based on individual profiles plotting the MP of the GPS and all EMG signals acquired. The goodness of fit of the linear regressions was assessed by the coefficient of determination (R2), and a repeated measures ANOVA was used to detect changes. A linear trend was found in EMG activity during submaximal speed runs (R2 = 1), but when the sprint effort was considered, the trend became exponential (R2 = 0.89). The EMG/force ratio displayed two different trends: linear up to a 30 m sprint (R2 = 0.99) and polynomial up to a 50 m sprint (R2 = 0.96). Statistically significant differences between the GPS and EMG were observed for MP splits at 0-5 m, 5-10 m, 25-30 m, 30-35 m, and 35-40 m and for EC splits at 5-10 m, 25-30 m, 30-35 m, and 35-40 m (p ≤ 0.05). Therefore, the determination of the MP and EC based on GPS technology underestimated the neuromuscular and metabolic engagement during the sprinting efforts. Thus, the EMG-derived method seems to be more accurate for calculating the MP and EC in this type of action.

Clinical gait analysis using video-based pose estimation: Multiple perspectives, clinical populations, and measuring change.

Gait dysfunction is common in many clinical populations and often has a profound and deleterious impact on independence and quality of life. Gait analysis is a foundational component of rehabilitation because it is critical to identify and understand the specific deficits that should be targeted prior to the initiation of treatment. Unfortunately, current state-of-the-art approaches to gait analysis (e.g., marker-based motion capture systems, instrumented gait mats) are largely inaccessible due to prohibitive costs of time, money, and effort required to perform the assessments. Here, we demonstrate the ability to perform quantitative gait analyses in multiple clinical populations using only simple videos recorded using low-cost devices (tablets). We report four primary advances: 1) a novel, versatile workflow that leverages an open-source human pose estimation algorithm (OpenPose) to perform gait analyses using videos recorded from multiple different perspectives (e.g., frontal, sagittal), 2) validation of this workflow in three different populations of participants (adults without gait impairment, persons post-stroke, and persons with Parkinson's disease) via comparison to ground-truth three-dimensional motion capture, 3) demonstration of the ability to capture clinically relevant, condition-specific gait parameters, and 4) tracking of within-participant changes in gait, as is required to measure progress in rehabilitation and recovery. Importantly, our workflow has been made freely available and does not require prior gait analysis expertise. The ability to perform quantitative gait analyses in nearly any setting using only low-cost devices and computer vision offers significant potential for dramatic improvement in the accessibility of clinical gait analysis across different patient populations.

Incentive mechanism of multiple green innovation behaviors of equipment manufacturing enterprises: A managers, green coordination groups and employees perspective.

Employees play a pivotal role in the implementing of green development strategies and the attainment of dual-carbon objectives within manufacturing enterprises. Effective motivation of employees, fostering consensus on environmental protection, increased engagement in environmental initiatives, and the cultivation of employee cohesion are all vital for fostering green development within these enterprises. This paper seeks to elucidate the roles of general managers, green coordination groups (GCG), and employees in actualizing green behaviors. Furthermore, it advocates for a double incentive model to be employed in the implementing of green strategies within manufacturing enterprises. The research reveals that multiple factors, including incentive intensity, green capability, effort cost, risk aversion, and green variance, significantly influence the formulation of incentive contracts for green behaviors. The motivation level of the general manager directly impacts the efforts of the GCG, the organization's green climate, the manager's individual efforts, and indirectly influences the motivation and efforts of employees towards green behaviors. Notably, the influence of the organization's green climate on employees surpasses than on the manager, underscoring the imperative for collaboration efforts between the general manager and GCG to instill green behaviors among employees. Hence, it is imperative for the general manager and GCG to collaborate not only on critical aspects of green strategy implementation but also in fostering green behaviors among employees. This collaboration will facilitate the development of a multi-layer incentive mechanism aimed at promoting and facilitating the adoption of green behaviors among employees, thus contributing to the advancement of theory regarding employees' green behaviors and offering practical guidance for effectively realizing dual-carbon targets and achieving high-quality development within enterprises.

Distinct roles of autonomy satisfaction and frustration in predicting adolescent students’ academic motivation and achievement

We examined whether autonomy satisfaction and frustration could be empirically distinguished and had different predictive relationships with students’ academic motivation and achievement in maths and English. Results based on a group of 3142 Chinese adolescent students revealed that autonomy satisfaction and frustration were two distinguishable constructs and demonstrated distinct predictive utility. Specifically, satisfaction of autonomy was positively associated with self-efficacy, which in turn, led to higher achievement. Furthermore, autonomy satisfaction was positively linked to interest value. In contrast, frustration of autonomy was positively associated with effort cost, which subsequently undermined achievement. Furthermore, these patterns were highly consistent across two subject domains. Findings of the present study highlight the importance of differentiating between autonomy satisfaction and frustration when predicting students’ academic outcomes.

Using a Modified Delphi Approach to Explore California’s Possible Transportation and Land Use Futures

Many methods exist for engaging experts in interactive groups to explore, clarify, and/or decide on various issues. In an investigation of four possible future scenarios concerning transportation and land use in California, we developed a novel “hybrid policy Delphi” method for use with a panel of 18 experts. We applied it to explore the policies and practices that would likely lead to each of the four scenarios and the consequences that would result from them. Through our process, panel members discussed and reflected on the scenarios in multiple ways. The scenario they considered most desirable they also deemed least likely to occur, and they foresaw the likely trajectory of California transportation and land use leading to less desirable scenarios. Our mix of discussion and questionnaires traded the benefit of anonymity for the benefit of exploratory, interactive discussion. In addition, our use of surveys before and after meetings allowed us to track changes in panel opinion on a central question and discuss the survey results at meetings, at the cost of greater administrative effort. We discuss the results of this hybrid policy Delphi approach, reflect on how it worked, and conclude with a discussion of limitations and future directions.

Design and Development of Multifunction Floor Cleaning Robot

Abstract— In response to the pressing challenges posed by the high cost of labour, time, and effort in developing countries, there has been a longstanding reliance on Multifunction Floor Cleaning Robot. Recognizing the need for more affordable and sustainable solutions, our innovative project focuses on the design, development, and manufacturing of a multifunction floor cleaning robot. This robot operates efficiently on battery, or electricity, providing flexibility and accessibility in diverse environments. The key objectives of this paper revolve around minimizing energy consumption, reducing both robot and operational costs, alleviating human effort, promoting environmental sustainability, and ensuring ease of handling. This not only contributes to an eco-friendlier approach but also facilitates the feasibility of constructing the robot on a commercial scale in the future. Keywords— regenerative braking, BLDC motor, inverter, battery.

Slowing of Movements in Healthy Aging as a Rational Economic Response to an Elevated Effort Landscape.

Why do we move slower as we grow older? The reward circuits of the brain, which tend to invigorate movements, decline with aging, raising the possibility that reduced vigor is due to the diminishing value that our brain assigns to movements. However, as we grow older, it also becomes more effortful to make movements. Is age-related slowing principally a consequence of increased effort costs from the muscles, or reduced valuation of reward by the brain? Here, we first quantified the cost of reaching via metabolic energy expenditure in human participants (male and female), and found that older adults consumed more energy than the young at a given speed. Thus, movements are objectively more costly for older adults. Next, we observed that when reward increased, older adults, like the young, responded by initiating their movements earlier. Yet, unlike the young, they were unwilling to increase their movement speed. Was their reluctance to reach quicker for rewards due to the increased effort costs, or because they ascribed less value to the movement? Motivated by a mathematical model, we next made the young experience a component of aging by making their movements more effortful. Now the young responded to reward by reacting faster but chose not to increase their movement speed. This suggests that slower movements in older adults are partly driven by an adaptive response to an elevated effort landscape. Moving slower may be a rational economic response the brain is making to mitigate the elevated effort costs that accompany aging.

A generating absorbing boundary condition for simulating wave interaction with maritime structures in current or at forward speed

The lack of suitable boundary conditions in practical surface wave simulations with maritime structures in current or at forward speed may cause energy in the computational domain to accumulate due to spurious wave reflection. The common way to prevent wave reflection is to use passive wave absorbers, such as damping zones or relaxation zones, which requires larger domains at the cost of computational effort. Our goal is to derive a local generating absorbing boundary condition (GABC) for long-crested irregular waves on top of a mean flow, using the flow to model the forward speed of a structure such as a ship. Earlier work has demonstrated that a local GABC for free surface waves has a performance similar to passive wave absorbers, but at a reduced computational effort. New in the present work is that we extend, verify and validate the GABC in the presence of a nonzero mean flow. The GABC is designed to be accurate for a range of wave components in irregular sea states, with the resulting reflection coefficients for each component lower than a chosen value, say 5%. Having used potential flow theory for its derivation means that the boundary should not be placed at the exact location where wave breaking is expected, such as very close to the structure in the domain, or in the surf zone in coastal modeling. For the application with ships in this article that does not pose a limitation. The performance is demonstrated for a range of dimensionless wave number between 0 and 6. Such a boundary condition is obtained through a rational approximation of the linear dispersion relation with a mean flow, in combination with vertical derivatives of the solution variables along the boundary. Local linearization means that the GABC incorrectly considers bound, nonlinear wave components to be freely propagating wave components. Bound components, however, tend to have smaller amplitudes and do not appear to affect performance for the considered cases. Results of simulations with regular and irregular waves, on top of flows with different magnitudes and directions, are found to agree with the theory. The main source of differences is the implementation of the second derivate in the GABC near the free surface. Simulations of a Wigley hull at forward speed in irregular waves are compared to an experiment that was conducted specifically for validating the ABC. The data of the experiment are available as open data through doi: 10.4121/21320604. The comparison between simulation and experiment demonstrates that the GABC with a mean flow can be applied not only for theoretical simulations with propagating waves, but also for more practical applications with a structure in the domain.

Benefit distribution of guaranteed water saving management contract based on principal-agent theory

Aiming at benefit distribution of guaranteed water saving management contract (WSMC) projects, principal-agent theory is used to propose benefit distribution scheme. Firstly, principal-agent models are established in two cases: (1) the water user and WSCO are risk-neutral; (2) the water user is risk-neutral, while WSCO is risk-averse. Then the models are solved by the backward induction method under symmetric information and asymmetric information. The models' results are analyzed and the results show that (1) WSCO's benefit distribution proportion is negatively correlated with effort cost coefficient, risk aversion degree and project uncertainty; (2) the water user's expected utility is positively correlated with project investment scale and WSCO's water saving capacity; (3) WSCO's risk aversion will reduce the water user's expected utility; (4) incentives are only required when WSCO's effort is unobservable. Finally, numerical examples are used to show the above results' rationality and suggestions are given for the water user and WSCO.

Neuroscience: Therapy modulates decision-making in Parkinson’s disease

There is mounting evidence that decision-making can be affected by treatment in Parkinson's disease. A new study shows that dopamine and deep brain stimulation, two mainstay treatments of Parkinson's, differently affect how patients make decisions weighing rewards against effort costs.

What rationale would work? Unfolding the role of learners’ attitudes and motivation in predicting learning engagement and perceived learning outcomes in MOOCs

The aim of this study is to gain insight into the interplay between attitudes, motivation, learning engagement, and perceived learning outcomes in massive open online courses (MOOCs). An online survey was administered to 232 MOOC learners. This study provided comprehensive explanations for individual differences in learning engagement and perceived learning outcomes in MOOCs with a modified model of the expectancy-value theory of achievement motivation. The structural equation modeling revealed that attitudes served as a precursor of participation in MOOCs that significantly influenced self-efficacy, intrinsic value, and task effort cost; self-efficacy and intrinsic value were positively associated with both learning engagement and perceived learning outcomes, while attitudes toward MOOC learning was positively related to perceived learning outcomes only. Furthermore, the mediation analyses highlighted that intrinsic value was a powerful mediator, which positively influenced the effects of attitudes and self-efficacy on learning engagement and perceived learning outcomes. The moderation analyses discovered that task effort cost moderated the effects of attitudes on learning engagement and perceived learning outcomes. Curriculum designers and instructors could benefit from this study to understand what rationales drive individuals to be engaged in MOOC learning and to reach greater perceived learning outcomes in MOOCs.