Integrated evaluation of the performance of phosphogypsum recycling technologies in China

The Chinese government is implementing policies, such as the "Guidance on comprehensive utilization of bulk solid waste for the 14th Five-Year Plan period", to stimulate phosphogypsum (PG) reduction and recycling. Thus, the comprehensive evaluation of PG recycling technologies for sustainable development is crucial. This study proposes a novel multi-criteria decision analysis (MCDA) method that considers the criteria of resources, environment, economy, and society and risk attitudes of decision-makers and integrates game theory (GT) and utility theory for criteria weighting and ranking to assess industrial-scale PG recycling technologies in China. The results demonstrate that GT provides more reasonable criteria weights than individual weighting methods. PG-based lightweight plaster is the top performer in the resource and environmental dimensions owing to its exceptional resource and energy efficiency. PG utilized for dry-mix mortar and organic fertilizer production exhibited the best utility performance of 0.74 and 0.73, respectively. Measures, such as subsidies and product publicity, should be implemented to promote these technologies. However, technologies with poor performance, such as PG used for the co-production of sulfuric acid and fertilizer or cement, may require optimization or substitution for the sustainable recycling of PG. The proposed MCDA method is robust and can serve as a reliable decision-making tool for other waste-recycling technologies. However, caution must be exercised when determining risk attitude using the MCDA method as it may vary with the number of technologies and affect the final rankings.

Psychological value theory: A computational cognitive model of charitable giving

Charitable giving involves a complex economic and social decision because the giver expends resources for goods or services they will never receive. Although psychologists have identified numerous factors that influence charitable giving, there currently exists no unifying computational model of charitable choice. Here, we submit one such model, based within the strictures of Psychological Value Theory (PVT). In four experiments, we assess whether charitable giving is driven by the perceived Psychological Value of the recipient. Across all four experiments, we simultaneously predict response choice and response time with high accuracy. In a fifth experiment, we show that PVT predicts charitable giving more accurately than an account based on competence and warmth. PVT accurately predicts which charity a respondent will choose to donate to and separately, whether a respondent will choose to donate at all. PVT models the cognitive processes underlying charitable donations and it provides a computational framework for integrating known influences on charitable giving. For example, we show that in-group preference influences charitable giving by changing the Psychological Values of the options, rather than by bringing about a response bias toward the in-group.

Energy expenditure does not solely explain step length-width choices during walking

Healthy young adults have a most preferred walking speed, step length and step width that are close to energetically optimal. However, people can choose to walk with a multitude of different step lengths and widths, which can vary in both energy expenditure and preference. Here, we further investigated step length-width preferences and their relationship to energy expenditure. In line with a growing body of research, we hypothesized that people's preferred stepping patterns would not be fully explained by metabolic energy expenditure. To test this hypothesis, we used a two-alternative forced-choice paradigm. Fifteen participants walked on an oversized treadmill. Each trial, participants performed two prescribed stepping patterns and then chose the pattern they preferred. Over time, we adapted the choices such that there was 50% chance of choosing one pattern over another (equally preferred). If people's preferences are based solely on metabolic energy expenditure, then these equally preferred stepping patterns should have equal energy expenditure. In contrast, we found that energy expenditure differed across equally preferred step length-width patterns (P<0.001). On average, longer steps with higher energy expenditure were preferred over shorter and wider steps with lower energy expenditure (P<0.001). We also asked participants to rank a set of shorter, wider and longer steps from most preferred to least preferred, and from most energy expended to least energy expended. Only 7/15 participants had the same rankings for their preferences and perceived energy expenditure. Our results suggest that energy expenditure is not the only factor influencing a person's conscious gait choices.

Evaluating Biosignatures for Life Detection

Conceptual frameworks are developed for evaluating the ability of different biosignatures to provide evidence for the presence of life in planned missions or observational studies. The focus is on intrinsic characteristics of biosignatures in space environments rather than on their detection, which depends on technology. Evaluation procedures are drawn from extensive studies in decision theory on related problems in business, engineering, medical fields, and the social arena. Three approaches are particularly useful. Two of them, Signal Detection Theory and Bayesian hypothesis testing, are based on probabilities. The third approach is based on utility theory. In all the frameworks, knowledge about a subject matter has to be translated into probabilities and/or utilities in a multistep process called elicitation. We present the first attempt to cover all steps, from acquiring knowledge about biosignatures to assigning probabilities or utilities to global quantities, such as false positives and false negatives. Since elicitation involves human judgment that is always prone to perceptual and cognitive biases, the relevant biases are discussed and illustrated in examples. We further discuss at which stage of elicitation human judgment should be involved to ensure the most reliable outcomes. An example, how evaluating biosignatures might be implemented, is given in the Supplementary Information.

Active inference and epistemic value

We offer a formal treatment of choice behavior based on the premise that agents minimize the expected free energy of future outcomes. Crucially, the negative free energy or quality of a policy can be decomposed into extrinsic and epistemic (or intrinsic) value. Minimizing expected free energy is therefore equivalent to maximizing extrinsic value or expected utility (defined in terms of prior preferences or goals), while maximizing information gain or intrinsic value (or reducing uncertainty about the causes of valuable outcomes). The resulting scheme resolves the exploration-exploitation dilemma: Epistemic value is maximized until there is no further information gain, after which exploitation is assured through maximization of extrinsic value. This is formally consistent with the Infomax principle, generalizing formulations of active vision based upon salience (Bayesian surprise) and optimal decisions based on expected utility and risk-sensitive (Kullback-Leibler) control. Furthermore, as with previous active inference formulations of discrete (Markovian) problems, ad hoc softmax parameters become the expected (Bayes-optimal) precision of beliefs about, or confidence in, policies. This article focuses on the basic theory, illustrating the ideas with simulations. A key aspect of these simulations is the similarity between precision updates and dopaminergic discharges observed in conditioning paradigms.

Cognitive science contributions to decision science

This article briefly reviews the history and interplay between decision theory, behavioral decision-making research, and cognitive psychology. The review reveals the increasingly important impact that psychology and cognitive science have on decision science. One of the main contributions of cognitive science to decision science is the development of dynamic models that describe the cognitive processes that underlay the evolution of preferences during deliberation phase of making a decision.

Estimating utility values for vesicoureteral reflux in the general public using an online tool

INTRODUCTION

Cost-utility analyses are useful to study conditions without a widely accepted treatment algorithm; in pediatric urology, one such condition is vesicoureteral reflux (VUR). A necessary component of cost-utility analyses is to accurately calculate the "utility", a numerical surrogate of quality of life, for various health states. Our aims were to determine utility values for representative VUR health states and to verify the feasibility of a novel online platform for utility elicitation in order to reduce the time and expense of such analyses.

METHODS

A cross-sectional survey of American adults was conducted using the time-trade-off (TTO) method. Respondents were recruited from an online work interface, Amazon's Mechanical Turk (MTurk). Four annualized VUR health states were assessed: VUR treated with/without continuous antibiotic prophylaxis (CAP) and with/without associated febrile urinary tract infection (UTI). A 6-week post-operative scenario following open ureteroneocystostomy was also assessed.

RESULTS

We received 278 survey responses (70% response rate). The respondents were largely between the ages of 25 and 44 (59%), female (60%), and Caucasian (76%). Thirty-seven percent had a college degree, and 44% were parents. Compared with a perfect health state of 1.0, we found mean utilities of 0.87 for VUR, regardless of whether CAP was used or whether UTI was present (p=0.9). The immediate post-operative period following ureteroneocystostomy garnered an annualized utility of 0.94.

CONCLUSIONS

Our data suggest that MTurk-based utility assessment is feasible, and that subjects view the VUR health state as only slightly inferior to perfect health. This includes VUR health states incorporating CAP and febrile UTI.