Preference Relations Research Articles

Population preferences for AI system features across eight different decision-making contexts.

Artificial intelligence systems based on deep learning architectures are being investigated as decision-support systems for human decision-makers across a wide range of decision-making contexts. It is known from the literature on AI in medicine that patients and the public hold relatively strong preferences in relation to desirable features of AI systems and their implementation, e.g. in relation to explainability and accuracy, and in relation to the role of the human decision-maker in the decision chain. The features that are preferred can be seen as 'protective' of the patient's interests. These types of preferences may plausibly vary across decision-making contexts, but the research on this question has so far been almost exclusively performed in relation to medical AI. In this cross-sectional survey study we investigate the preferences of the adult Danish population for five specific protective features of AI systems and implementation across a range of eight different use cases in the public and commercial sectors ranging from medical diagnostics to the issuance of parking tickets. We find that all five features are seen as important across all eight contexts, but that they are deemed to be slightly less important when the implications of the decision made are less significant to the respondents.

The Sexually Dichromatic Use of Chromatophores for Cryptic Coloration in the Shrimp Neopontonides beaufortensis.

AbstractSexual dimorphism typically arises as a result of sexual selection or sex-specific natural selection. Species that exhibit cryptic coloration provide an excellent system for studying sex-specific selection for sexual dichromatism. In this study, we examined the sexually dichromatic use of chromatophores in the seawhip shrimp, Neopontonides beaufortensis (Borradaile, 1920), which commonly resides on colonies of Leptogorgia virgulata (Lamarck, 1815), a gorgonian octocoral that occurs in multiple color morphs. We documented the frequency of cryptic coloration in N. beaufortensis and tested colony color preference in relation to their current color. In the field, individuals always matched the color of the L. virgulata colony they were found on or were largely translucent. However, when given a choice, individuals chose colonies at random, independent of color. Additionally, we quantified locations across the bodies of males and females that differ most in chromatophore usage and tested the ability of both sexes to change color over 7 days. Females housed with L. virgulata colonies that differed in color from their starting color changed their coloration over the 7 days to better match the colony, while males remained translucent regardless of the color of colony they were housed with. Neopontonides beaufortensis individuals differed most in their coloration in regions corresponding to the saddle region and areas of the abdomen, locations in which females carry their eggs during development. These findings provide insight into the ecological factors underlying sexual dichromatism and shed light on the potential sex-specific selective mechanisms responsible for sexually dimorphic traits.

Generating Diverse Optimal Road Management Plans in Post-Disaster by Applying Envelope Multi-Objective Deep Reinforcement Learning

The authors used a data-driven reinforcement learning model for the post-disaster rapid recovery of human mobility, considering human-mobility recovery rate, road connectivity, and travel cost as the recovery components, to generate the reward framework. Each component has relative importance with respect to the others. However, if the preference is different from the original one, the optimal policy may not always be identified. This limitation must be addressed to enhance the robustness and generalizability of the proposed deep Q-network model. Therefore, a set of optimal policies were identified over a predetermined preference space, and the underlying importance was evaluated by applying envelope multi-objective reinforcement learning. The agent used in this study could distinguish the importance of each damaged road based on a given relative preference and derive a road-recovery policy suitable for each criterion. Furthermore, the authors provided the guidelines for constructing the optimal road-management plan. Based on the generalized policy network, the government can access diverse restoration strategies and select the most appropriate one depending on the disaster situation.

Pareto Set Reduction Based on Information about Type Two Fuzzy Preference Relation. Algorithm Description

Pareto Set Reduction Based on Information about Type Two Fuzzy Preference Relation. Algorithm Description

Group decision-making method based on expert credibility with multi-granularity probabilistic linguistic Z-number preference relation

Group decision-making method based on expert credibility with multi-granularity probabilistic linguistic Z-number preference relation

Pareto Set Reduction Based on Information about Type Two Fuzzy Preference Relation. Algorithm Justification

Pareto Set Reduction Based on Information about Type Two Fuzzy Preference Relation. Algorithm Justification

Abstract A100: Large-scale cell line profiling of small molecule MAPK pathway inhibitors identifies important differences between therapeutics acting on the same biochemical target

Abstract The mitogen-activated protein kinase (MAPK) pathway is frequently dysregulated in cancer, leading to unrestricted cell growth. Inhibitors that specifically target key components of the pathway, such as B-RAF and MEK inhibitors, have been approved for treatment of V600E-mutant melanoma, while inhibitors of G12C-mutant K-RAS, have been approved for lung cancer. Several dimer-selective pan-RAF inhibitors, and inhibitors of other components in the pathway, such as ERK and G12D-mutant K-RAS, are currently in clinical development. Cancer cell panel profiling, in combination with genomics, proteomics and bioinformatics, was performed to get more insight into mechanistic differences of small molecules acting on the same primary target, and to study the role of cell-type specific factors. Approximately twenty inhibitors of either RAF, MEK, ERK, or RAS were profiled in nine-point duplicate dose ranges in cell viability assays of more than hundred human cancer cell lines that have been derived from diverse tumor tissues (the Oncolines® panel). The half-maximal inhibitory concentration (IC50) calculated from the dose-response curves in the cell viability assays was used to relate drug response to genetic, genomic and (phospho-)proteomic features in the cancer cell lines. Oncogenic alterations in MAPK components, including BRAF, KRAS, NRAS, and MAP2K1 mutations, were represented in multiple cell lines of the panel, and were related to drug response. Additionally, to identify cell-intrinsic transcriptomic or proteomic factors that predict response to the inhibitors, the relationship between drug response and basal gene and protein expression levels (as reported in the DepMap database) was analyzed. Lastly, cell line responses to the different inhibitors were correlated with the DepMap cell line CRISPR knockout dataset, enabling the identification of genes whose dependency most closely resembles the response to inhibitors of the MAPK pathway. Our approaches unveiled subtle but important differences in cell line targeting between inhibitors acting on the same biochemical target, such as the relative preference of belvarafenib to target B-RAF-mutant cell lines, which was not seen for naporafenib. Our results may help guiding the development and application of precision medicine strategies in the context of MAPK pathway-targeted therapies. Citation Format: Jeffrey J. Kooijman, Awan Al Koerdi, Wilhelmina E. van Riel, Esmee van den Bossche, Jelle Dylus, Jeroen A.D.M. de Roos, Janneke J.T.M. Melis, Guido J.R. Zaman. Large-scale cell line profiling of small molecule MAPK pathway inhibitors identifies important differences between therapeutics acting on the same biochemical target [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr A100.

Factors Affecting Patient and Caregiver Preferences for Treatment of Myeloma and Indolent Lymphoma.

Treatment options for myeloma and indolent lymphoma are increasing exponentially, with distinct efficacy, side effects, and cost. We aim to determine the factors influencing patient and caregiver treatment preferences. Patients and caregivers of patients with myeloma and indolent lymphoma were recruited from two cancer centers in Singapore. Preferences were elicited using a discrete choice experiment. Attributes and levels were selected based on a previous qualitative study. The relative preference for levels within each attribute (part worth utility values) and the extent to which an attribute would influence decision making (relative importance) were calculated. Patient and caregiver participation in the treatment plan selection process were assessed using the Control Preference Scale. One hundred ninety-nine patients and 169 caregivers were recruited. Patients placed the highest importance on out-of-pocket costs (relative importance = 35%), followed by efficacy (25%), persistent side effects (19%), administration route (8%), treatment duration (7%), and short-term side effects (5%). Caregivers ranked efficacy (27%) as the most important attribute, over out-of-pocket costs (24%). Most patients preferred a collaborative role in the shared decision-making process, while similar proportions of caregivers favored active and collaborative roles. Our study demonstrates that both patients and caregivers consider cost seriously when making treatment decisions. Furthermore, as patient and caregiver preferences may differ, there are implications for treatment selection and counseling, especially in cultures where caregivers have more prominent roles in treatment planning.

Factors influencing acceptance of family planning methods among women coming to immunization OPD: a cross sectional study

Background: Family planning is one of the most cost-effective interventions. Therefore, different factors influencing reasons behind non acceptance of family planning are necessary to be known in order to formulate good plans and policies. Methods: This study was a cross-sectional study conducted at immunization clinic of urban area. Systematic random sampling method was used. A pre-determined questionnaire was administered. Data was analysed using SPSS 22. Results: Only 42.63% women adopted family planning methods. The statistically significant predictors for uptake of family planning services are knowledge of contraceptives (p=0.000), school education (p=0.002), prior use of contraceptives (p=0.001) and age of mother. The reasons for non-acceptance of family planning practices were fertility related (21.2%), lack of knowledge (19.7%), opposition from family members (16.9%), breastfeeding (14.5%), not having intercourse (12%), method related side effects (8.5%) and preference to specific gender (2.1%). Conclusions: According to age group and number of children to women should be motivated by the health worker for the appropriate contraception choice and reasons for non-acceptance of family planning methods form the basis for the qualitative research studies.

Does pain hurt more in Spanish? The neurobiology of pain among Spanish-English bilingual adults.

We previously found Spanish-English bilingual adults reported higher pain intensity when exposed to painful heat in the language of their stronger cultural orientation. Here, we elucidate brain systems involved in language-driven alterations in pain responses. During separate English- and Spanish-speaking fMRI scanning runs, 39 (21 female) bilingual adults rated painful heat intermixed between culturally evocative images and completed sentence reading tasks. Surveys of cultural identity and language use measured relative preference for US-American vs Hispanic culture (cultural orientation). Participants produced higher intensity ratings in Spanish compared to English. Group-level whole-brain differences in pain-evoked activity between languages emerged in somatosensory, cingulate, precuneus and cerebellar cortex. Regions of interest associated with semantic, attention and somatosensory processing showed higher average pain-evoked responses in participants' culturally preferred language, as did expression of a multivariate pain-predictive pattern. Follow-up moderated mediation analyses showed somatosensory activity mediated language effects on pain intensity, particularly for Hispanic oriented participants. These findings relate to distinct ('meddler', 'spotlight' and 'inducer') hypotheses about the nature of language effects on perception and cognition. Knowledge of language influences on pain could improve efficacy of culturally sensitive treatment approaches across the diversity of Hispanic adults to mitigate documented health disparities in this population.

Incomplete interval-valued probabilistic uncertain linguistic preference relation in group decision making

In group decision making (GDM), due to complexity of various factors, decision makers (DMs) often provide incomplete preference relations (PRs) in preference matrix. Interval-valued probabilistic uncertain linguistic term set (IVPULTS) is a flexible and accurate tool to depict evaluation information of experts. In this paper, we mainly propose a new concept pertaining to interval-valued probabilistic uncertain linguistic preference relation (IVPULPR) that applies the IVPULTS to preference relations. Firstly, some new basic theoretical concepts of IVPULTS are developed including ordered IVPULTS, normalization method and new expectation function. Secondly, we establish several goal programming models to estimate the unknown elements in incomplete IVPULPR and propose the expected additive consistency of IVPULPR. To improve the consistency level, two optimization models are constructed based on the idea of minimum adjustment. Thirdly, we derive the experts’ weights in terms of information uncertainty, where a new method to measure information uncertainty of IVPULTS is proposed. For the sake of improving group consensus, we construct a group consensus index (GCI) and two optimization models depending on the adjustment mechanism of expert weight. Finally, a complete GDM framework with incomplete IVPULPR is devised based on the analysis of IVPULPR consistency and group consensus. Through an experiment analysis by using an UCI dataset, we find that the proposed GDM model can not only precisely express fuzzy preference information of DMs, but also ensure achievement of acceptable consistency and group consensus under the condition of not changing the initial preference as much as possible.

Labour shortages and employer preferences in retaining and recruiting older workers

PurposeThis article investigates whether employers are more likely to employ older workers when faced with a shortage of qualified labour. Furthermore, it analyses whether in such cases age stereotypes moderate employers' preferences towards four employment options: (1) supporting workers to continue until the retirement age, (2) encouraging workers to continue beyond the retirement age, (3) recruiting someone older than 55 and (4) (re)hiring someone who has retired.Design/methodology/approachData were drawn from a survey conducted among Finnish employers in 2021 (response rate = 66%, N = 1,442). Applying factor analysis to questions about older workers' qualities compared to those of average workers, a distinction was made between perceptions of experience-related and adaptability-related qualities. Generalised ordered logistic regression models were estimated to analyse the relations of preferences for each employment option with experiencing recruitment problems, workplace age stereotypes and interactions between these.FindingsExperiencing recruitment problems was positively related to preferences for hiring a retired person. Employers with difficulties in recruitment were more likely to support work until the retirement age and recruit someone over 55, but only if they had above-average positive perceptions of older workers' experience-related qualities. Employers confronted with recruitment difficulties were more likely to encourage workers to continue beyond the retirement age if they had more positive perceptions of older workers' adaptability-related qualities.Originality/valueThis study shows that, even when confronted with labour shortages and population ageing, workplace age stereotypes still pose a potential obstacle for employers to make the best use of an older workforce.

International Remittances and the Labour Market in Peru

International remittances are a relevant source of income in developing countries, with important implications for the labour market of recipient countries. Peruvian international migration is a particular case of Latin America, since it tends to be concentrated in middle-and high-income households and in highly educated people, who display particular preferences in relation to the labour market. Using data from 2004 to 2019, we analysed the impact of remittances on employment, hours worked, and wages of Peruvian workers. Our results show that remittances reduce labour participation by 9.8 percentage points (pp). On average, the effect is greater among dependent workers than self-employed workers (-7.5 pp versus -3 pp). Similarly, we observed an increase in hourly income in both types of work (10.1% and 65%, respectively). In this sense, the Peruvian case offers a new perspective on the effect of remittances on the labour market, where despite having most of its labour force in informal jobs and self-employment, it does not encourage employment in those sectors, as occurred in previous studies.

Public Perception of Green Supply Chains and Its Impact on Customer Behavior: An Empirical Analysis

The public is increasingly becoming aware of environmental challenges and adjusting its purchasing behavior in pursuit of sustainable products and services. To compete in the global scene, firms need to transform their supply chains to adhere to eco-friendly practices. This study focuses on the electronics market, which is distinctively interesting due to its small product life cycles, high-end capabilities, and fierce competition. A novel research model comprising nine hypotheses that attempt to investigate and assess the factors influencing customers’ perceptions and purchasing preferences in relation to green supply chains in the electronics industry was developed. We conducted field research to test the model empirically using survey data from 147 individuals with different backgrounds. The dataset was verified and validated by means of explanatory factor analysis. Structural equation modeling analysis was performed that revealed the linkage between demographics (age), willingness to pay, purchasing intention, and green consumerism. Other research findings included the intricate interconnections between environmental concern, knowledge, attitude, customers’ perceptions/effectiveness, and behavior. This research gives insights into green consumerism in the electronics sector, and its managerial implications can guide sustainable supply chain practices and customer-centric marketing approaches.

Supporting students to engage with case studies: a model of engagement principles

ABSTRACT Case studies are an educational tool that can promote active learning, and make learning more accessible, by serving as frameworks for student meaning-making. This action research project focused on the student experience of case studies; aiming to understand how students respond to being taught with case studies, whether they are able to engage with cases and learn from them, and how educators can support this engagement and learning, through the effective use of cases. The findings of this project are of value to any educators working with case studies in the classroom, or considering doing so. The research included an initial survey, to ascertain student experience and preferences in relation to case studies, and review practical considerations. This informed content and approach for two observed tutorials, which used a case study to support final-year UK undergraduates in their learning about formal and informal workplace communication. The project concluded with a further survey to capture student perspectives on the case study itself, and the tutorial experience. The findings from all stages allowed a model for case study teaching to be developed, as a guide for educators. The key considerations for educators are that applicable, relevant and real-life case studies effectively support engagement and learning. Furthermore, focused case studies are preferred, with greater depth than breadth. Finally, practical considerations supporting accessibility should not be overlooked, the appearance and presentation of the case study were significant, as was the provision of time for preparation or reading.

Three-way group consensus with experts' attitudes based on probabilistic linguistic preference relations

Intelligent decision-making collaborates with big data analytics to navigate the intricate landscape of the digital economy, orchestrating data-driven strategies to achieve the most favorable results. Through the integration of specific objectives and relevant data, intelligent decision-making involves the modeling, analysis, and realization of decisions. This comprehensive process seamlessly incorporates elements such as constraints, strategies, preferences, and uncertainty, ultimately leading to the autonomous achievement of optimal outcomes. In this context, the probabilistic linguistic preference relation (PLPR) serves as a recently introduced form of linguistic evaluations, offering adaptable expression of expert preference assessments. Within the domain of preferences, consistency emerges as a pivotal consideration. Extremes occur when calculating the additive consistency of PLPR using expectation values. To comprehensively address the trouble, this paper introduces an innovative planning model that employs deviation degrees. The establishment of a consistency threshold is approached objectively using the principle of minimum individual regret and maximum group delight. Once consistency is established, the process advances to consensus reaching process (CRP). During the consensus feedback phase, the infusion of the three-way decision (TWD) theory accounts for distinct expert modification attitudes, while ensuring consistency remains upheld throughout the modification procedure. For clarity, the proposed technique is referred to as the TWD-GC-EA method. Notably, the effectiveness of the designed approach is demonstrated through its application to a real-world scenario. Furthermore, a comparative assessment is conducted against several other consensus methods to validate its efficacy and superiority.

On Kemeny Optimization Scheme for Fuzzy Set of Relations

The present paper investigated the aggregation of individual preferences into a group fuzzy preference relation for a fuzzy set of decision-makers (DMs). This aggregation is based on the Kemeny optimization scheme. It was proven that this group relation is a Type-2 fuzzy relation (T2FR). The decomposition approach was used to analyze the group T2FR. It is shown that the group T2FR can be decomposed according to secondary membership grades into a finite collection of Type-1 fuzzy relations. Each of them is a group fuzzy relation for a crisp set of DMs, which is the corresponding α-cut of the original fuzzy set of DMs. Illustrative examples are given.

Critical risk factors of public building green retrofit projects- an empirical study in Chongqing, China

ABSTRACT In order to discuss the critical risk factors of green retrofit project in existing public buildings, this study identifies the risk factors from the whole life cycle firstly, and the experts are invited to assess the probability of the occurrence, the degree of the severity, and the follow-up effect of the risk occurrence, respectively. In addition, a Choquet integral-based FMEA (Failure mode and effect analysis) model is introduced to assess and analyze the risks in which the descriptive language results are transformed into triangle fuzzy number to analyze the risk assessment results quantitatively, and the relative preference relations are used to rank the risk factors, empirical study is conducted focusing on Chongqing. Based on the proposed risk assessment model, the top 10 high-risk factors in green retrofit projects of public buildings are extracted, the possible potential causes are analyzed, and the corresponding risk response measures are proposed, which provide references for the improvement of risk management in urban renewal.

Representation of a preference relation on convex metric spaces by a numerical function

In this work, we study the interplay of ordered relation and the structure of the convex metric space on which it is defined: First, we show when a convex metric space is isomorphic with a convex subset of some vector space. Second, we obtain conditions for a representation of a preference relation on a convex metric space.

Mean values as nondominated multicriterial points

AbstractIn this paper, we introduce new notions of mean values based on ideas of multicriteria optimization. The distances between the current point to all points in the sample are regarded as elements of a vector estimate. Such vector estimates are usually scalarized, for example, by taking the sum of all components. In contrast, we introduce preference relations on the set of all such vectors, based on the information about the preferences of the decision maker who could be a statistician, analyst or researcher. Such preference relations reflect the distances between points, including the case in which all distances are equally important. We define the mean values as the points whose corresponding vector estimates are nondominated with respect to the defined preference relation, and investigate their properties. Such mean values turn out to be multi‐valued. We further explore the relationship between the new notions of mean values with their conventional definitions and suggest computational approaches to the calculation of the suggested new means. We also outline generalisations of the suggested approach to the case of multidimensional data.