Search

The importance of shared decision making (SDM) for informed consent has been emphasised in the updated regulatory guidelines. Errors of completion, legibility and omission have been associated with paper-based consent forms. We introduced a digital consent process and compared it against a paper-based process for quality and patient reported involvement in shared decision making. 223 patients were included in this multi-site, single centre study. Patient consent documentation was by either a paper consent form or the Concentric digital consent platform. Consent forms were assessed for errors of legibility, completion and accuracy of content. Core risks for 20 orthopaedic operations were pre-defined by a Delphi round of experts and forms analysed for omission of these risks. SDM was determined via the 'collaboRATE Top Score', a validated measure for gold-standard SDM. 72% (n = 78/109) of paper consent forms contained ≥1 error compared to 0% (n = 0/114) of digital forms (P < 0.0001). Core risks were unintentionally omitted in 63% (n = 68/109) of paper-forms compared to less than 2% (n = 2/114) of digital consent forms (P < 0.0001). 72% (n = 82/114) of patients giving consent digitally reported gold-standard SDM compared to 28% (n = 31/109) with paper consent (P < 0.001). Implementation of a digital consent process has been shown to reduce both error rate and the omission of core risks on consent forms whilst increasing the quality of SDM. This novel finding suggests that using digital consent can improve both the quality of informed consent and the patient experience of SDM. • The paper consent process is associated with errors and omissions of core risks. • A digital consent process improved error rate and omission rate of core risks. • Patients reported a higher level of shared decision making with a digital process. • Documentation of consent can be reliably standardised with an electronic record. [ABSTRACT FROM AUTHOR]

The incidence of differentiated thyroid cancer (DTC) has been increasing worldwide, mostly, as an increase in the incidental detection of micro papillary thyroid carcinomas (microPTCs), many of which are potentially overtreated, as suggested by the unchanged mortality. Several international guidelines have suggested a less aggressive approach. More recently, it has been shown that active surveillance or minimally invasive treatments (MIT) are good alternatives for the management of these patients. In this context, patient participation in the decision-making process is paramount. The Endocrine Task Force of the European Organisation for Research and Treatment of Cancer (EORTC) has undertaken the task to establish consensus and define its position based on the scientific evidence concerning, 1) the current state of diagnostic and management options in microPTCs, including the current opinion of physicians about shared decision making (SDM), 2) the available evidence concerning patients' needs and the available decision instruments, and 3) to provide practical suggestions for implementation of SDM in this context. To improve SDM and patients' participation, knowledge gaps and research directions were highlighted. • New management approaches for patients with low-risk microPTC have been introduced. • For all available options, scientific evidence is weak, resulting in clinical equipoise. • SDM to carefully discuss these treatment options with patients is paramount. [ABSTRACT FROM AUTHOR]

In recent years, the pulp and paper industry has changed a lot and products have been constructed in quite different methods using new technologies. It can be due to the emergence of challenges and constraints such as shortage of raw materials, energy consumption (fossil fuels, electric, etc.), management of the resulting pollutants, environmental issues, ongoing legal requirements and cleaner production strategies. In Iran, the pulp and paper industry's technological development is not keeping pace with global growth. Iran's pulp and paper mills supply a small fraction of domestic market. The reasons can be due to old technologies being used in factories, aging machinery, low productivity of production systems and lack of coordination with modern technologies. It leads to low-quality of paper products and willingness to buy local products. The aim of this study is to select the most appropriate technologies in the pulp section, due to high impact of pulp quality on the quality of final paper. Using a 2-filterd fuzzy decision-making, hierarchical structure of research is designed to assess technological alternatives according to the selected criteria. Findings show that after passing through two filters, Kraft method was chosen as the most appropriate method. The Kraft process has still many advantages like the high quality of the produced pulp and self-sufficiency in energy supply. This framework offers an appropriate procedure for identifying and selecting technologies that has not been used in past researches. Using this framework facilitates using a clear procedure for evaluating and selecting technology and prevents future losses for organizations. [ABSTRACT FROM AUTHOR]

Numerous socio-legal factors make the process of surrogate decision-making for people living in dementia very complicated in Japan. In this discussion paper, we argue that the lack of early consultation between patients, surrogate decision-makers and healthcare providers and the overreliance of patients and their families on doctors to assume the decision-making role lead to healthcare practices that may not align with the patient's wishes. Further, we argue that lack of laws on surrogate decision-making, changing family structure and the liabilities associated with the care of people living with dementia contribute to the complexity of the decision-making process in Japan. Finally, given the rapidly changing social and healthcare norms in Japan, we call for greater involvement of nurses and care workers in the decision-making process to ensure patient-centric treatment and care are adopted. [ABSTRACT FROM AUTHOR]

LCA studies on waste management have been promoted as they can help policy makers choose the best environmental options. However, the increasing globalization of raw materials and waste makes the optimization of waste management strategies and policies quite challenging. Therefore, new approaches are needed in order to identify the consequences of markets on the waste management systems. This paper concentrates on the quantification of greenhouse gas (GHG) emissions of recycling processes. The aim is to generate a comprehensive assessment of GHG emissions as a consequence of increasing the amount of material collected for recycling. Consequential life cycle assessment (CLCA) is an effective methodological framework for addressing GHG quantifications within market, but to properly perform and assess all of the market links between raw materials and waste, it is necessary to determine the cause-effect chains made up of physical flows. Thus, we propose integrating the methodologies of material flow analysis (MFA) and CLCA. We applied these methodologies to the paper and cardboard recycling system in Spain. The GHG results varied between −36 kg CO 2 eq. and −317 kg CO 2 eq. per ton of waste paper collected, depending on the quantity of waste paper exported and the source of marginal pulp considered. The cumulative energy demand (CED) was also calculated as complementary indicator. Similar trends as for GHG emissions were obtained. The future GHG quantifications should be based on the flows described by MFA analysis and should be quantified using CLCA because methodologies that accurately account for GHG are necessary for decision-making. [ABSTRACT FROM AUTHOR]

Modern day societies and economies are becoming increasingly vulnerable to the continued erosion of the stocks and flows of essential ecosystem services. Thus, the management of complex socio-economic systems to effectively provide these essential services has become a global priority policy and academic research area. Understanding how underlying processes and functions contribute towards the provision of final ecosystem services can facilitate improved dissemination of credible, legitimate and salient information to decision-makers. This paper presents an ecosystem service value chain analysis framework that applies basic system dynamics modelling in the form of causal loop diagrams to facilitate an alternative analysis of ecosystem service value chains. A scoping application of the framework is applied to a case study for flood attenuation services in the Baviaanskloof catchment in South Africa. The framework enables the identification of forward linkages and ripple effects in individual value chains of final ecosystem services as well as the identification and assessment of challenges and opportunities within individual causal pathways. Ultimately, providing the potential to advance strategies for improving the efficiency and effectiveness of final ecosystem service provision. [ABSTRACT FROM AUTHOR]

The design of a high-volume printer for professional use is rather complex. The design of the paper path and the timing of sheets is frequently reengineered as the design of the printer components progresses. This paper presents an optimization model for the combined paper path and timing design problem. The paper path is an optimal physical dimensioning problem, while the timing is an open-loop optimal control problem. The coupled optimization problem is formulated as a simultaneous analysis and design (SAND) problem using a direct transcription of the optimal control problem. Benefits of the chosen formulation for industrial application are the ease of setting up the optimization model for arbitrary printer configurations, and the short computation times. Results of an industrial case are presented. [ABSTRACT FROM AUTHOR]

Introduction : In pursuit of sustainability goals, many cities are introducing measures to increase the usage of bicycles as a means of transportation. City planners aim to ensure that this increase does not lead to an increase in crashes, but must make corresponding infrastructure decisions with limited information. Sufficient data to perform a statistical analysis of location-specific crash frequencies is rarely available. For example, only approximately 10% of all bicycle crashes are reported to the police (Shinar et al., 2018). Therefore, urban planners often rely on expert opinion, which may lead to suboptimal prioritization and realization of infrastructure improvements. Method: This paper demonstrates how surveys on bicycle crashes can be used to aid urban planners in making infrastructure decisions. In addition to confirming the location and characteristics of reported crashes, surveys can uncover characteristics of crashes that are not reported to the police, situations in which a crash almost occurred, and locations perceived by cyclists to be dangerous. Surveys also allow urban planners to investigate non-infrastructure related causes of crashes, such as the frequency with which individual cyclists use other modes of transportation. Practical Applications: The usefulness of surveys in the determination of urban cycling safety is demonstrated in this paper through analysis of survey results from the city of Zurich in 2018. [ABSTRACT FROM AUTHOR]

• Healthcare demand change is investigated from the view of the economic and societal dynamics. • The differentiated risk attitudes of individuals and groups are considered. • An extended PageRank algorithm are applied to determine the weights of experts. • An improved GLDS method is developed to prioritize healthcare risk. • A conflict analysis is established to show PIR between failure modes. Faced with backward and uneven economic conditions and an irrational and increasingly inequitable social structure, healthcare disparities are widening and the healthcare inequalities are expanding. This can lead to an increasing public demand for healthcare services, posing unprecedented risk, such as resource shortages, quality deterioration and rising healthcare costs. By identifying, managing, and optimizing the aforementioned risks within the healthcare system, it helps the healthcare system better address the challenges of expanding healthcare demands under evolving economic and social structure. To achieve this, this paper employs failure mode and effects analysis (FMEA) to identify severe failure modes in healthcare services. However, traditional FMEA methods possess limitations in assessing the dynamics of trust relationships and interaction effects among experts within social networks. Therefore, this paper proposes an improved gained and lost dominance score (GLDS) based social network decision-making method considering risk attitudes for FMEA to prioritize failure modes in healthcare services. First, transform linguistic risk assessment information from an interdisciplinary team of experts based on probabilistic linguistic term sets handle uncertain efficiently. Meanwhile, experts' influence is reflected by an extended PageRank algorithm with trust degrees based on social networks analysis. Next, an improved GLDS method considering the differentiated risk attitudes of individuals and groups is developed to prioritize failure modes. Especially, to solve the problems of soft preference and incomparability relation among failure modes, which are ignored by the traditional GLDS method, a conflict analysis is established to determine the preference, indifference, and incomparability relations. Finally, the practicality of the proposed method is illustrated by the healthcare service risk case in the emergency department and the effectiveness of the developed method is validated by comparison and sensitivity experiments. The results suggest that failure to update labels showing patient severity promptly is the most dangerous. In addition, it would be more economically efficient to analyze the non-comparable failure modes facing different risk factors. [ABSTRACT FROM AUTHOR]

Evidence-based published data is the prime source used for clinical decision making, the issuance of guidelines and the drafting new policies. A number of different study designs are used to perform and publish research studies, corresponding to the research question being investigated. Over the decades, a hierarchical system of evidence has been established. This provides an indication of the level of evidence each study design contributes to the research community. Policies and clinical guidelines should naturally be based on the highest level of evidence data available. However, the highest level of evidence study designs may not always provide an adequate answer to a research question. Thus, when utilising published evidence-based data, one should first understand the clinical question that needs to be answered, and then critically appraise the published data accordingly. [ABSTRACT FROM AUTHOR]

Abstract: Recycling activities have demonstrated a remarkable increase over the last decade due to the economic and environmental dimensions of sustainability. In particular, capacity planning in production facilities has become a strategic issue of key importance affecting the profitability of the recycling industry. By integrating the simulation discipline and the feedback control theory into a dynamic consideration of recycling networks, this paper proposes a System Dynamics (SD) model for strategic capacity planning in the recycling industry. The decision-making process is based on a balanced tradeoff between profit and capacity utilization for a single producer with closed-loop recycling activities. The SD model captures physical stocks and flows apparent in real-world recycling networks and includes the feedback mechanisms which regulate these flows. When used as an “experimental tool”, the model tests alternative capacity planning policies and demonstrates policy suggestions for the forward and reverse channels, which maximize profitability over a strategic planning horizon. This experimentation is illustrated by using data from a paper producer with recycling activities, as a real-world test case. Extensive simulation runs, investigate the efficiency of a wide range capacity acquisition decisions, using total company profit as the measure of performance. Although such an analysis may differ from one recycling network to another, it has been kept as generic as possible to facilitate its applicability to a wide-spectrum of real-world local, regional or global networks. [Copyright &y& Elsevier]

Cumulative risk assessments (CRAs) examine potential risks posed by exposure to multiple and sometimes disparate environmental stressors. CRAs are more resource intensive than single chemical assessments, and pose additional challenges and sources of uncertainty. CRAs may examine the impact of several factors on risk, including exposure magnitude and timing, chemical mixture composition, as well as physical, biological, or psychosocial stressors. CRAs are meant to increase the relevance of risk assessments, providing decision makers with information based on real world exposure scenarios that improve the characterization of actual risks and hazards. The U.S. Environmental Protection Agency has evaluated a number of CRAs, performed by or commissioned for the Agency, to seek insight into CRA concepts, methods, and lessons learned. In this article, ten case studies and five issue papers on key CRA topics are examined and a set of lessons learned are identified for CRA implementation. The lessons address the iterative nature of CRAs, importance of considering vulnerability, need for stakeholder engagement, value of a tiered approach, new methods to assess multiroute exposures to chemical mixtures, and the impact of geographical scale on approach and purpose. [ABSTRACT FROM AUTHOR]

The vision of a sustainable and safe use of chemicals to protect human health, preserve the environment and maintain the ecosystem requires innovative and more holistic approaches to risk assessment (RA) in order to better inform decision making. Integrated risk assessment (IRA) has been proposed as a solution to current scientific, societal and policy needs. It is defined as the mutual exploitation of environmental risk assessment (ERA) for human health risk assessment (HHRA) and vice versa in order to coherently and more efficiently characterize an overall risk to humans and the environment for better informing the risk analysis process. Extrapolating between species which are relevant for HHRA and ERA requires a detailed understanding of pathways of toxicity/modes of action (MoA) for the various toxicological endpoints. Significant scientific advances, changes in chemical legislation, and increasing environmental consciousness have created a favourable scientific and regulatory environment to develop and promote the concept and vision of IRA. An initial proof of concept is needed to foster the incorporation of IRA approaches into different chemical sectorial regulations and demonstrate their reliability for regulatory purposes. More familiarity and confidence with IRA will ultimately contribute to an overall reduction in in vivo toxicity testing requirements. However, significant progress will only be made if long-term support for MoA-related research is secured. In the short term, further exchange and harmonization of RA terminology, models and methodologies across chemical categories and regulatory agencies will support these efforts. Since societal values, public perceptions and cultural factors are of increasing importance for the acceptance of risk analysis and successful implementation of risk mitigation measures, the integration of socio-economic analysis and socio-behavioural considerations into the risk analysis process may help to produce a more effective risk evaluation and consideration of the risks and benefits associated with the use of chemicals. [ABSTRACT FROM AUTHOR]

Background: Electronic data collection is increasingly being used for discrete choice experiments (DCEs).Objectives: To study whether paper or electronic administration results in measurement effects.Methods: Respondents were drawn from the same sample frame (an Internet panel) and completed a nearly identical DCE survey either online or on paper during the same period. A DCE on preferences for basic health insurance served as a case study. We used panel mixed logit models for the analysis.Results: In total, 898 respondents completed the survey: 533 respondents completed the survey online, whereas 365 respondents returned the paper survey. There were no significant differences with respect to sociodemographic characteristics between the respondents in both samples. The median response time was shorter for the online sample than for the paper sample, and a smaller proportion of respondents from the online sample were satisfied with the number of choice sets. Although some willingness- to-pay estimates were higher for the online sample, the elicited preferences for basic health insurance characteristics were similar between both modes of administration.Conclusions: We find no indication that online surveys yield inferior results compared with paper-based surveys, whereas the price per respondent is lower for online surveys. Researchers might want to include fewer choice sets per respondent when collecting DCE data online. Because our findings are based on a nonrandomized DCE that covers one health domain only, research in other domains is needed to support our findings. [ABSTRACT FROM AUTHOR]

• There has been a limited scope of investigation of the contextual factors affecting driver decision-making during narrow passage interactions. • The study found that the likelihood of giving way may alter due to characteristics of the interaction partners, including their vehicle type. • It was also found that factors, external to the direct interaction partners, may affect the likelihood of giving way, such as the presence of vehicles beyond the direct interaction partners. • This paper validates previous communication findings in a UK context. Narrow passage interactions have received increased attention from academics seeking to create behavioural models of the interaction and those looking to define how autonomous vehicles (AVs) should interact with their human counterparts in a composite road system. Despite this increased attention, many factors remain unexplored in the narrow passage literature, with the literature also encompassing few driving culture contexts. To this end, this study employs an explorative survey to identify additional factors that affect driver decision-making during narrow passage interactions, as well as driver perceptions of different communications in a UK context. The study's 243 participants were presented with a range of different narrow passage scenarios and asked to indicate how likely they were to give way/yield to a vehicle approaching the narrow passage from the opposite direction. In addition, they also completed the Multidimensional Driving Style Inventory to identify their driving styles and asked to identify which signals they look for from their interaction partner during narrow passage interactions, as well as the meaning of those signals. The results of the study show that situational characteristics such as the vehicle type being interacted with, being in a rush and being followed by vehicles alter the likelihood of drivers giving way at narrow passages, whilst a person's driving style can also indicate how likely someone is to give way to another vehicle. These results highlight the factors that are considered by drivers, increasing our understanding of the factors that need to be incorporated in driver behaviour models and in AV development. [ABSTRACT FROM AUTHOR]

Doctors in Star Trek are vital and central characters, often crucial in helping their captains to reach command decisions. They are also interdisciplinarians, performing not only medical tasks but also any form of work related to all fields of biology. Furthermore, these doctors also carry out any required research that pertains to the biological sciences. It is perhaps this unique blend of skills, combined with a fundamental orientation towards humanism and compassion, that leads to their default position, de facto, if not de jure, as the crew's ethics officers, a role that they embrace with as much dedication and zeal as the former Soviet communist political officers/commissars (the Zampolit) did theirs. This paper will show that from the very inception of Star Trek, doctors strictly adhered to deontological tenets which lead them to actively influence command decisions that pertain not only to health, but also to any ethical decisions that may have to be taken by Starfleet officers. This portrayal of future doctors signals the wishes of contemporary audiences: that future doctors remain humane, compassionate and ethical guardian angels, and not only superb medics. [ABSTRACT FROM AUTHOR]

Highlights: [•] Theoretically placing strategic communication management within the DRR paradigm. [•] Defining DR4 in the South African environment. [•] Indicating the need for DR4 communication in the South African environment. [ABSTRACT FROM AUTHOR]

Abstract: Computer-based interventions are being used more in the classroom. Student responses to these interventions often contribute to decisions making regarding important outcomes. It is important to understand the effect of these interventions within the context of the intervention as well as across related context. The current study examined the generalization of math fact fluency gains resulting from a computer-based intervention to paper-and-pencil performance. A total of 31 second grade students completed fluency drills on the computer or with paper and pencil. Pretest–posttest performance on both computer and paper and pencil for all students was evaluated using a doubly multivariate repeated measure ANOVA. Results indicated that gains achieved on the computer did not generalize to paper-and-pencil performance. [Copyright &y& Elsevier]

This paper concerns problem formulation and solution procedure for inventory planning with Markov decision process models. Using data collected from a large paper manufacturer, we develop inventory policies for the finished products. To incorporate both variability and regularity of the system into mathematical formulation, we analyze probabilistic distribution of the demand, explore its connection with the corresponding Markov chains, and integrate these into our decision making. In particular, we formulate the Markov decision model by identifying the chain''s state space and the transition probabilities, specify the cost structure and evaluate its individual component; and then use the policy-improvement algorithm to obtain the optimal policy. Application examples are provided for illustration. [Copyright &y& Elsevier]

Abstract: Study results are often presented as abstracts at scientific conferences before publication as full articles in peer-reviewed journals. Given the current emphasis on evidence-based decision-making, it is vital that the peer-reviewed literature represents as broad and un-biased a selection of studies as possible. While the proportion of abstracts published as full papers in the peer-reviewed literature has been extensively studied in human healthcare, no such studies have been published in the field of food safety. The goal of this study was to estimate the proportion published and average time to publication for conference abstracts involving studies of pre-harvest or abattoir interventions to reduce foodborne pathogens. Abstracts were obtained by hand-searching available proceedings between 1995 and 2004 from 10 conferences. Included abstracts were limited to those detailing non-observational, controlled in vivo trials where outcome(s) were measured in livestock, carcasses or eggs. Data on abstract type (≤500 words, >500 words), species, intervention, study type, sample size, number housed together and outcomes were recorded. Four databases (Agricola, CAB, Web of Science, Scholar''s Portal) were searched for published papers corresponding to the conference abstracts using author and intervention/pathogen terms. Time to publication and overall median time to publication were estimated. Chi-squared, logistic regression and survival analyses were used to test for significant differences in proportion published and time to publication between variable levels. Of the 149 abstracts identified, 68 (45.6%) were published in peer-reviewed journals within 4 years. The median time to publication was 13.5 months (range: 0, 72). Abstracts shorter than 1 page were significantly more likely to be published (OR=2.2, 95% CI=1.0, 4.8), and abstracts involving pork or pigs were significantly less likely to be published that those involving poultry (OR=0.4: 0.2, 0.8). Abstracts reporting at least one positive outcome were more likely to be published (OR=2.608: 1.097, 6.196) and were published faster (HR=2.3: 1.1, 4.7). Time to publication decreased with the number of positive outcomes reported (HR=1.1: 1.0, 1.3). Sample size could only be determined for 46% of abstracts, with a median sample size of 9 (range 1–378), and housing was sufficiently described to determine sample size in 35% of pre-slaughter studies. The potential effects of this bias on systematic reviews and uses of interventions could be significant, and thus improvements may be warranted in the proportion of conference abstracts resulting in papers in the peer-reviewed literature. [Copyright &y& Elsevier]

Highlights: [•] Consistency in the identification, assessment and management of ED substances is needed. [•] Scientifically robust weight-of-evidence approaches for regulatory decision making are needed. [•] More debates on socioeconomic benefits in the context of decision making are needed. [ABSTRACT FROM AUTHOR]

Objectives: To synthesize the findings of cognitive interview and usability studies performed to assess the measurement equivalence of patient-reported outcome (PRO) instruments migrated from paper to electronic formats (ePRO), and make recommendations regarding future migration validation requirements and ePRO design best practice.Methods: We synthesized findings from all cognitive interview and usability studies performed by a contract research organization between 2012 and 2015: 53 studies comprising 68 unique instruments and 101 instrument evaluations. We summarized study findings to make recommendations for best practice and future validation requirements.Results: Five studies (9%) identified minor findings during cognitive interview that may possibly affect instrument measurement properties. All findings could be addressed by application of ePRO best practice, such as eliminating scrolling, ensuring appropriate font size, ensuring suitable thickness of visual analogue scale lines, and providing suitable instructions. Similarly, regarding solution usability, 49 of the 53 studies (92%) recommended no changes in display clarity, navigation, operation, and completion without help. Reported usability findings could be eliminated by following good product design such as the size, location, and responsiveness of navigation buttons.Conclusions: With the benefit of accumulating evidence, it is possible to relax the need to routinely conduct cognitive interview and usability studies when implementing minor changes during instrument migration. Application of design best practice and selecting vendor solutions with good user interface and user experience properties that have been assessed in a representative group may enable many instrument migrations to be accepted without formal validation studies by instead conducting a structured expert screen review. [ABSTRACT FROM AUTHOR]

Abstract: Game theory provides a solution to the problem of finding a set of optimal decision-making strategies in a group. However, people seldom play such optimal strategies and adjust their strategies based on their experience. Accordingly, many theories postulate a set of variables related to the probabilities of choosing various strategies and describe how such variables are dynamically updated. In reinforcement learning, these value functions are updated based on the outcome of the player''s choice, whereas belief learning allows the value functions of all available choices to be updated according to the choices of other players. We investigated the nature of learning process in monkeys playing a competitive game with ternary choices, using a rock–paper–scissors game. During the baseline condition in which the computer selected its targets randomly, each animal displayed biases towards some targets. When the computer exploited the pattern of animal''s choice sequence but not its reward history, the animal''s choice was still systematically biased by the previous choice of the computer. This bias was reduced when the computer exploited both the choice and reward histories of the animal. Compared to simple models of reinforcement learning or belief learning, these adaptive processes were better described by a model that incorporated the features of both models. These results suggest that stochastic decision-making strategies in primates during social interactions might be adjusted according to both actual and hypothetical payoffs. [Copyright &y& Elsevier]

In this position paper, we shall undertake a critical scrutiny of the decision analysis (DA) paradigm on the basis of experience we gained from working on the bullwhip effect. We had some success with sorting out the complexities of the bullwhip by using fuzzy numbers in the bullwhip models, and we found out that this points the way to a more viable approach to sort out complex decision problems. As a positive criticism of the DA paradigm we have collected the insights we have gained in an agenda for soft decision analysis (SDA), which we hasten to add is not complete but—hopefully—an opening for focused research and continuing development. [Copyright &y& Elsevier]

A major concern with Bayesian decision making under uncertainty is the use of a single probability measure to quantify all relevant uncertainty. This paper studies prior robustness as a form of continuity of the value of a decision problem. I show that this notion of robustness is characterized by a form of stable choice over a sequence of perturbed decision problems, in which the available acts are perturbed in a precise fashion. I then introduce a choice-based measure of prior robustness and apply it to models of climate mitigation and portfolio choice. • Belief Robustness and Continuity: Beliefs are "robust" if minor changes in beliefs lead to minor changes in choices. This notion can be tested by evaluating perturbations of feasible bets. • Measure of Robustness: A comparative measure of belief robustness can quantify the sensitivity of optimal choices to parametric assumptions. • Impact on Key Economic Models: The measure shows that heavy-tailed distributions yield more robust choices in portfolio and economy-climate models, highlighting its practical importance. [ABSTRACT FROM AUTHOR]

In this paper, the problem of multiplayer hierarchical decision-making problem for non-affine systems is solved by adaptive dynamic programming. Firstly, the control dynamics are obtained according to the theory of dynamic feedback and combined with the original system dynamics to construct the affine augmented system. Thus, the non-affine multiplayer system is transformed into a general affine form. Then, the hierarchical decision problem is modeled as a Stackelberg game. In the Stackelberg game, the leader makes a decision based on the information of all followers, whereas the followers do not know each other's information and only obtain their optimal control strategy based on the leader's decision. Then, the augmented system is reconstructed by a neural network (NN) using input–output data. Moreover, a single critic NN is used to approximate the value function to obtain the optimal control strategy for each player. An extra term added to the weight update law makes the initial admissible control law no longer needed. According to the Lyapunov theory, the state of the system and the error of the weights of the NN are both uniformly ultimately bounded. Finally, the feasibility and validity of the algorithm are confirmed by simulation. [ABSTRACT FROM AUTHOR]

• Life Cycle Engineering has been demonstrated as a viable approach for space mission design. • The life cycle sustainability impacts of SmallSats have been benchmarked for the first time. • Multi-Criteria Decision Analysis is a useful technique for identifying significant hotspots. • Improvements measures are more successful with increased levels of participant interaction. The application of Life Cycle Engineering (LCE) within the concurrent engineering process presents a viable method for assessing environmental, social and economic impacts of space missions. Despite this, the novelty of the concept within space mission design has meant that the approach has not yet been widely implemented. This paper successfully demonstrates this technique for the first time and presents LCE results of three SmallSat missions designed at the University of Strathclyde using the concurrent engineering approach. The Strathclyde Space Systems Database (SSSD) was deployed to calculate the total life cycle impacts of each mission, including the identification of common design hotspots. A novel technique called Multi-Criteria Decision Analysis (MCDA) was also trialled, whereby several impact categories were converted into single scores as a test case to reduce the learning curve for engineers. Overall, the LCE results indicate that the manufacturing & production of the launcher dominate the majority of impact categories. Other common hotspots were found to relate to the use of germanium as a substrate as well as the launch event. As an additional observation, in terms of the behavioural aspects, it was clear that study participants were more open to the concept of LCE with each new concurrent engineering session, evidenced by increasing levels of interaction amongst study participants. These findings are intended to provide industrial stakeholders with a preliminary benchmark relating to the general sustainability footprint of SmallSats, whilst demonstrating the viability of integrating LCE within the concurrent engineering process of space missions. [ABSTRACT FROM AUTHOR]

The Wiener index of a strong digraph D is defined as the sum of the shortest path distances between all ordered pairs of vertices. This definition has been extended to digraphs that are not necessarily strong by defining the distance from a vertex a to a vertex b as 0 if there is no path from a to b in D. Knor et al. (2016) [9] considered (not necessarily strong) orientations of graphs with maximum Wiener index. The authors conjectured that for a given tree T , an orientation D of T of maximum Wiener index always contains a vertex v such that for every vertex u , there is either a (u , v) -path or a (v , u) -path in D. In this paper we disprove the conjecture. We also show that the problem of finding an orientation of maximum Wiener index of a given graph is NP-complete, thus answering a question by Knor et al. (2016) [8]. We briefly discuss the corresponding problem of finding an orientation of minimum Wiener index of a given graph, and show that the special case of deciding if a given graph on m edges has an orientation of Wiener index m can be solved in time quadratic in the order of the graph. [ABSTRACT FROM AUTHOR]

• Propose an end-of-use condition estimation method based on reliability and warranty policy. • Present a two-stage optimization model for the Re -X decision-making problem. • Develop a condition-based end-of-use processing policy under demand uncertainty. • Reduce lifecycle cost and environmental impact for product family. • Demonstrate the methodology with case study and result analysis. The concept of circular economy has been diffused in recent decades to promote economic growth that does not add to the burden on natural resource extraction. Re -X options (e.g., reuse, repair, refurbish, remanufacture, recycle) have been gradually adopted in the product development process and optimized to reduce or eliminate waste and pollution. Although manufacturing incorporating Re -X options can be more environmentally friendly, it involves more sources of uncertainty than traditional manufacturing since the end-of-use products can be collected from multiple origins with various quantities and qualities, and the market demand for both new and remanufactured products cannot be forecasted perfectly. Thus, there is a need to optimize the Re -X policy to alleviate the negative impacts of the higher uncertainty. One option is using the reliability information of new products to estimate the end-of-use conditions and applying multi-stage stochastic optimization to capture multiple demand scenarios. This paper develops a two-stage stochastic optimization model to optimize the quality thresholds for reuse, recycling, and remanufacturing options. Our objective is to minimize the total cost, energy consumption, and environmental impact of producing and providing warranty service for a product family. The model employs reliability information of product components to estimate the warranty service cost and the end-of-use conditions of the returned resources. A case study on a general product family is implemented to illustrate the efficacy of the optimization model. Results show that the two-stage optimization can achieve cost and environmental impact reduction for a hybrid manufacturing and remanufacturing process. [ABSTRACT FROM AUTHOR]

Abstract: Land-use change (LUC) estimated by economic models has sparked intense international debate. Models estimate how much LUC might be induced under prescribed scenarios and rely on assumptions to generate LUC values. It is critical to test and validate underlying assumptions with empirical evidence. Furthermore, this modeling approach cannot answer if any specific indirect effects are actually caused by biofuel policy. The best way to resolve questions of causation is via scientific methods. Kim and Dale attempt to address the question of if, rather than how much, market-induced land-use change is currently detectable based on the analysis of historic evidence, and in doing so, explore some modeling assumptions behind the drivers of change. Given that there is no accepted approach to estimate the global effects of biofuel policy on land-use change, it is critical to assess the actual effects of policies through careful analysis and interpretation of empirical data. Decision makers need a valid scientific basis for policy decisions on energy choices. [Copyright &y& Elsevier]

Abstract: Objective: This article discusses the identification, selection, and refinement of topics for comparative effectiveness systematic reviews within the Agency for Healthcare Research and Quality''s Effective Health Care (EHC) program. Study Design and Setting: The EHC program seeks to align its research topic selection with the overall goals of the program, impartially and consistently apply predefined criteria to potential topics, involve stakeholders to identify high-priority topics, be transparent and accountable, and continually evaluate and improve processes. Results: A topic prioritization group representing stakeholder and scientific perspectives evaluates topic nominations that fit within the EHC program (are “appropriate”) to determine how “important” topics are as considered against seven criteria. The group then judges whether a new comparative effectiveness systematic review would be a duplication of existing research syntheses, and if not duplicative, if there is adequate type and volume of research to conduct a new systematic review. Finally, the group considers the “potential value and impact” of a comparative effectiveness systematic review. Conclusion: As the EHC program develops, ongoing challenges include ensuring the program addresses truly unmet needs for synthesized research because national and international efforts in this arena are uncoordinated, as well as engaging a range of stakeholders in program decisions while also achieving efficiency and timeliness. [Copyright &y& Elsevier]

Abstract: Several authors have highlighted the role of intuition in expertise. In particular, a large amount of data has been collected about intuition in expert nursing, and intuition plays an important role in the influential theory of nursing expertise developed by Benner [1984. From Novice to Expert: Excellence and Power in Clinical Nursing Practice. Addison–Wesley, Menlo Park, CA]. We discuss this theory, and highlight both data that support it and data that challenge it. Based on this assessment, we propose a new theory of nursing expertise and intuition, which emphasizes how perception and conscious problem solving are intimately related. In the discussion, we propose that this theory opens new avenues of enquiry for research into nursing expertise. [Copyright &y& Elsevier]

Abstract: Although children partition by repeatedly halving easily and spontaneously as early as the age of 4, multiplicative thinking is difficult and develops over a long period in school. Given the apparently multiplicative character of repeated halving and doubling, it is natural to ask what role they might play in the development of multiplicative thinking. We investigated this question by examining children''s solutions to folding tasks, which involved predicting the number of equal parts created by a succession of given folds and determining a sequence of folds to create a given number of equal parts. Analyzing a combination of cross-sectional data and case studies from standardized clinical interviews, we found that children were most successful at coordinating folding sequences with multiplicative thinking when they used a conceptualization of doubling based upon recursion. This conceptualization tended to generate more sophisticated solutions. [Copyright &y& Elsevier]

Robot sequential decision-making in the real world is a challenge because it requires the robots to simultaneously reason about the current world state and dynamics, while planning actions to accomplish complex tasks. On the one hand, declarative languages and reasoning algorithms support representing and reasoning with commonsense knowledge. But these algorithms are not good at planning actions toward maximizing cumulative reward over a long, unspecified horizon. On the other hand, probabilistic planning frameworks, such as Markov decision processes (MDPs) and partially observable MDPs (POMDPs), support planning to achieve long-term goals under uncertainty. But they are ill-equipped to represent or reason about knowledge that is not directly related to actions. In this article, we present an algorithm, called iCORPP, to simultaneously estimate the current world state, reason about world dynamics, and construct task-oriented controllers. In this process, robot decision-making problems are decomposed into two interdependent (smaller) subproblems that focus on reasoning to "understand the world" and planning to "achieve the goal" respectively. The developed algorithm has been implemented and evaluated both in simulation and on real robots using everyday service tasks, such as indoor navigation, and dialog management. Results show significant improvements in scalability, efficiency, and adaptiveness, compared to competitive baselines including handcrafted action policies. • This article formally introduces the Integrated Reasoning and Planning (IRP) problem for robots. An IRP problem has a factored state space that is specified by a set of endogenous and exogenous variables. • This article introduces a sequential decision-making algorithm, called Interleaved Commonsense Reasoning and Probabilistic Planning (iCORPP), for addressing IRP problems. • This article presents systematic evaluations of iCORPP using two tasks of mobile robot navigation, and spoken dialog systems, as demonstrated on a real robot. • This article builds on our previous research that appeared in two conference papers (Zhang and Stone, 2015; Zhang et al., 2017). This article unifies their terminology, problem statements, and algorithms. • Compared to our prior work, this article introduces a new problem statement in Section 4.1, which covers the problems addressed in both conference papers. • To address the IRP problem, we have reformulated the iCORPP algorithm (Section 4.2) into a novel form that includes the three key steps of "logical reasoning," "probabilistic reasoning over world states," and "probabilistic reasoning about world dynamics." [ABSTRACT FROM AUTHOR]

• The geographical factors cannot be ignored in the site selection of WTE plant. • SVNSs makes up for the weakness of traditional fuzzy sets in information description. • The weight calculation method in SVNSs background is proposed. • EDAS can reduce the adverse impact of decision makers' own reasons on the results. • The combination of GIS and MCDM can improve the precision of site selection. Waste-to-energy (WtE) plant has been attached great importance by more and more countries because of the harmless, energy reducing and recycling characteristics, and has become an important part of the city's normal operation and energy structure. Whereas, the reasonable site selection of the WtE plant is the key to ensure its sustainable development. This paper is designed to provide a two-stage model for the site selection of WtE plants. Firstly, a comprehensive assessment criteria system including environmental, economic, technical and social factors is established by selecting the reasonable influence criterias from the current relevant literature. Considering the fuzziness of the criteria and the bounded knowledge of decision makers, the single-valued neutrosophic sets (SVNSs) are introduced to describe the fuzzy information, and creatively combined with decision-making and trial evaluation laboratory-analytical network process (DANP) method to determine the influence grades of criterias and calculate the weights. After that, the relevant geographic information layers are collected and the preliminary alternatives are obtained by Geographic information system (GIS) from an overall perspective, then the extend evaluation based on distance from average solution (EDAS) method is utilized to rank the alternatives under the SVNSs environment. Finally, the model is tested to select the optimal alternative for siting the WtE plants in Beijing as an example. It is verified that the model is of great stability and feasibility by sensitivity analysis and comparative analysis. The result shows that this paper can provide a new theoretical basis for the planning of WtE plants. [ABSTRACT FROM AUTHOR]

Objective: To identify decision characteristics for which SDM authors deem SDM appropriate or not, and what arguments are used.Methods: We applied two search strategies: we included SDM models from an earlier review (strategy 1) and conducted a new search in eight databases to include papers other than describing an SDM model, such as original research, opinion papers and reviews (strategy 2).Results: From the 92 included papers, we identified 18 decision characteristics for which authors deemed SDM appropriate, including preference-sensitive, equipoise and decisions where patient commitment is needed in implementing the decision. SDM authors indicated limits to SDM, especially when there are immediate life-saving measures needed. We identified four decision characteristics on which authors of different papers disagreed on whether or not SDM is appropriate.Conclusion: The findings of this review show the broad range of decision characteristics for which authors deem SDM appropriate, the ambiguity of some, and potential limits of SDM.Practice Implications: The findings can stimulate clinicians to (re)consider pursuing SDM in situations in which they did not before. Additionally, it can inform SDM campaigns and educational programs as it shows for which decision situations SDM might be more or less challenging to practice. [ABSTRACT FROM AUTHOR]

• A new simulation methodology, intended bounded rationality methodology, is proposed. • Evaluation cost-benefit of different aspects of decision support techniques. • Classification of errors that a decision support technique can generate is proposed. • Consistent erroneous judgments and inconsistent correct judgments are possible. • A case where consistency condition in AHP provides maximum 5% of the expected return. Expert's judgments have been crucial in the development of decision theory; however, what criterion to use in the selection of experts remains an issue to address. Decision support techniques proposed to improve the quality of expert judgment decision making consider a demonstrated inconsistency of the judgments expressed by an expert as a criterion of exclusion in the decision-making process of such expert. Although consistency appears to be a desirable condition to qualify as "expert", little is known about the quality of the decisions made imposing consistency as the expert qualifying condition. This paper proposes a simulation methodology, based on an automaton programmed to make decisions in an intended but bounded rational way, to assess the cost-benefit of different aspects of decision support techniques. Within this methodology, the imposition of the consistency condition in the selection of experts is studied. In particular, the paper shows with a case study example that the Analytical hierarchy process (AHP) decision support technique expected payoff is at most 5% higher when implementing Saaty's consistency criterion of the expert's judgments than when the consistency criterion is not considered. [ABSTRACT FROM AUTHOR]

The CPR school has successfully rebutted Hardin''s pessimistic Tragedy of the Commons model. However, in recent years, critics have focussed on the inward orientation and lack of contextual analysis characterising the writings of the CPR school.Oakerson [A Model for the analysis of common property problems. Working Paper R86-13. Workshop in Political Theory and Policy Analysis, Indiana University, 1986] and Ostrom [Governing the Commons. Cambridge, Cambridge University Press, 1990] have detailed the list of variables that have to be studied to understand the mechanics of collective action. However, these factors are internal to the community. Recent critics'' point out that the actions of individual agents are also influenced by the alternatives embedded outside the system. These variables are collectively labelled contextual factors.In our paper, we have analysed the case of a fishermen''s cooperative in the Calcutta Metropolitan District to show how the historic and economic context shapes targets of resource users and affects the feasibility of alternative courses to achieve the target by determining opportunity and transaction costs of actions. This indicates the importance of contextual factors in explaining the formation and evolution of the resource regime. [Copyright &y& Elsevier]

Alpine skiing beginners are easily injured if they fail make the right decisions when faced with unexpected situations. Excellent decision-making requires extensive training, while alpine skiing training is limited by time and space. To address these issues, this paper combines VR and machine learning techniques to develop a high fidelity VR skiing decision-making training system based on HCPS framework. The aim is to train beginner skiers in decision-making by creating automated and repeatable virtual scenarios. Firstly, physical world (ski resort environment, and user motions) was mapped into the VR world using the HCPS framework. Afterwards, the user's decision motions were made based on the scenarios provided, while being identified through an improved SVM (94.5% accuracy). The motion recognition results were fed into the expert system to assess the feasibility of the decision-making. Finally, the feasibility of the system was assessed with a combination of subjective and objective approaches. The results showed that the VR system significantly improved the participants' skiing decision-making ability and speed compared to traditional 2D video training. The high fidelity environment reduced participants' motion sickness symptoms and resulted in a better sensory experience. In addition, participants were more focused in the high fidelity environment. Overall, these results demonstrated the construct validity of the virtual ski decision-making training system. This study changes the traditional training method to create an immersive training environment, and provides an effective avenue for the development of sports training. [Display omitted] • Designs processes and algorithmic models for virtual ski decision systems are presented. • Interaction between user and system via IMU and EEG signals. • The feasibility of the system is assessed through a combination of subjective and objective methods. • Voting classifier achieves higher action recognition rate. • VR training system improves decision-making skills and speed. [ABSTRACT FROM AUTHOR]

Cardiac Rehabilitation (CR) has become an established intervention to support patient recovery after a cardiac event, with evidence supporting its effectiveness and cost-effectiveness in improving patient health and reducing future burden on healthcare systems. However, this evidence has focussed on the national value case for CR rather than at the point at which it is commissioned. This analysis uses the UK as a case-study to explore variation in current CR engagement and disassemble the value case from a commissioner perspective. Using data collected by the National Audit of CR (NACR), and an existing model of cost-effectiveness, we present details on the current level of CR uptake by commissioning region (Specialist Clinical Networks) in light of the current UK target of achieving 85% uptake. We then interrogate the value case for achieving the target at a commissioner level, highlighting the expected profile of health benefits and healthcare system costs over the long-term. Importantly we consider where this may differ from the national value case. Each commissioning region has a unique level of CR uptake and sociodemographic profile. Concurrently, the value case for commissioning CR relies on the upfront cost of the service being offset by long-term healthcare savings, and health improvements. The shift in the UK and internationally to more localised commissioning necessitates evidence of cost-effectiveness that better reflects the realities of those decision makers. This paper provides vital additional data to facilitate such commissioners to understand the value case in increasing CR uptake in line with national policy. • Many nations are aiming to increase rates of CR uptake. • Commissioning of services is complex and different from national decision making. • The challenges in reaching targets are different for each region. • It is important to consider equity when commissioning CR. [ABSTRACT FROM AUTHOR]

When cognitive load exceeds cognitive capacity, individuals may make poorer decisions, especially when substantial deliberation is required. Deck and Jahedi's (2015) influential work on cognitive load found that individuals whose arithmetic performance is most impacted by high cognitive load become more risk averse, less patient and more subject to the anchoring effect. Since results of cognitive load manipulation studies are mixed, replication of influential studies is essential to strengthen our understanding of the effects of cognitive load. In this paper, we attempt to closely replicate Experiment 1 in Deck and Jahedi (2015). Though we observe similar effects of cognitive load on arithmetic performance, we fail to replicate their overall results on risky choice and impatience. While we are unable to clearly identify the reasons for this non-replication, the evidence points to subtle differences in the allocation of attention and effort across subject pools. [ABSTRACT FROM AUTHOR]

Joint decision-making can be seen as the synchronization of actions and emotions, usually via nonverbal interaction between people while they show empathy. The aim of the current paper was (1) to develop an adaptive computational model for the type of synchrony that can occur in joint decision-making for two persons modeled as agents, and (2) to visualize the two persons by avatars as virtual agents during their decision-making. How to model joint decision-making computationally while taking into account adaptivity is rarely addressed, although such models based on psychological literature have a lot of future applications like online coaching and therapeutics. We used an adaptive network-oriented modelling approach to build an adaptive joint decision-making model in an agent-based manner and simulated multiple scenarios of such joint decision-making processes using a dedicated software environment that was implemented in MATLAB. Programming in the Unity 3D engine was done to virtualize this process as nonverbal interaction between virtual agents, their internal and external states, and the scenario. Although our adaptive joint decision model has general application areas, we have selected a therapeutic session as example scenario to visualize and interpret the example simulations. [ABSTRACT FROM AUTHOR]

Abstract: The paper of Huang, Keisler and Linkov (HKL) () has motivated us to this note about the relation between ranking procedures and Multi-Criteria Decision Analysis (MCDA) tools. The key concept in the HKL-paper is in our eyes the ‘trade-off’. A ‘trade-off’ seems necessary, when conflicting indicator values are present. HKL stress that the general application of MCDA is hampered by different terminology. We do not claim to have a solution for that problem. Nevertheless, we think that the discussion is worthwhile and this note presents some of our ideas, which basically imply the need of a broadening of the definition of MCDA. [Copyright &y& Elsevier]

Carsharing services provide users with a new way of approaching mobility and accessing shared vehicles. Since the initial pilot studies in the early 90s, technological innovations (e.g., advances in mobile technology, increased range of electric cars) and the establishment of new business models (e.g, station-based, free-floating, peer-to-peer, packages by time and/or kilometres) helped branding carsharing as a sustainable yet flexible and personalized mobility alternative. On the other hand, the carsharing market today is extremely scattered, as it can include multiple operators, which are often in competition among each other. While this variety of operators provides the user with a variety of travel options, without proper coordination, this competition can reduce the efficiency of the carsharing market and, in extreme cases, of the entire transportation system. In this context, this paper studies the needs of travellers, local authorities, and carsharing service providers, and analyses how incentives can be used to align their goals. Taking Munich, Copenhagen, and Tel Aviv-Yafo as case studies, focus groups were used to identify thirteen different travellers' needs, which are grouped into five main categories: ownership issues, coverage area, financial aspects, vehicle settings, and integration of carsharing with other modes. Moreover, to understand the needs of service providers and public authorities, in-depth interviews were conducted. The results indicate that regulatory barriers, integration with other transport modes, and social equity issues are the most critical elements for the thriving of carsharing services. Our results also suggest that incentives can be divided into two main categories, namely direct and indirect incentives. With regards to direct incentives, parking stood out as the most important incentive. Among indirect incentives, those associated with the integration of carsharing with other transport services, were prominent. As part of the methodology, the results of the qualitative study are validated through a quantitative analysis. A bigger sample of the population answered an online survey, which was used to validate the list of potential incentives that can help aligning the goals of stakeholders and users. • Policy recommendations on how incentives can be used to support the decision making process. • A list of potential user-directed and stakeholder-directed incentives. • Incentives are classified into two different categories: direct and indirect. • The paper analyses three cities (Copenhagen - Denmark, Munich - Germany, and Tel Aviv-Yafo - Israel). • The results of the qualitative study are validated through a quantitative analysis. [ABSTRACT FROM AUTHOR]