Collective bargaining as a two-level game: Direct learner-expert interactions

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.In this article, the authors introduce a new feature to model the collective bargaining process: a two-level game setting with direct learner-expert interaction. In the simulation ZUG UM ZUG 2015, participants form union and management negotiation teams to negotiate with each other (first level) and with a management or union “tariff commission,” which has to approve proposed contracts (second level). To increase the degree of realism and the teaching effectiveness of the simulation, real-world negotiation experts negotiate in tariff commissions directly with participants. The authors also introduce a negotiation process to facilitate an efficient knowledge transfer from experts to learners

Physical Attractiveness, Opportunity, and Success in Everyday Exchange

28 pagesThe role of perceived physical attractiveness in everyday exchange is addressed using a laboratory paradigm that examines both play-versus- not-play and cooperate-versus-defect choices in an ecology of available prisoner’s dilemma games. The analysis considers the actions of both subject and other in encounters where exchange relationships are possible and include perceptions of others’ and own physical attractiveness. Results indicate that subjects are more likely to enter play and to cooperate with others they find attractive. Men who see themselves as more attractive more often cooperate than other men, while women who see themselves as more attractive less often cooperate than other women. In addition, subjects who rate themselves as highly attractive are more likely to cooperate with others they see as also highly attractive. Subjects expect others whom they see as attractive to cooperate more often. At the same time, the effect of perceived attractiveness on choice is independent of these expectations, supporting the hypothesis that attractiveness is a “taste” or “benefit” for actors in exchange relationships

Protein prediction for trait mapping in diverse populations

Genetically regulated gene expression has helped elucidate the biological mechanisms underlying complex traits. Improved high-throughput technology allows similar interrogation of the genetically regulated proteome for understanding complex trait mechanisms. Here, we used the Trans-omics for Precision Medicine (TOPMed) Multi-omics pilot study, which comprises data from Multi-Ethnic Study of Atherosclerosis (MESA), to optimize genetic predictors of the plasma proteome for genetically regulated proteome-wide association studies (PWAS) in diverse populations. We built predictive models for protein abundances using data collected in TOPMed MESA, for which we have measured 1,305 proteins by a SOMAscan assay. We compared predictive models built via elastic net regression to models integrating posterior inclusion probabilities estimated by fine-mapping SNPs prior to elastic net. In order to investigate the transferability of predictive models across ancestries, we built protein prediction models in all four of the TOPMed MESA populations, African American (n = 183), Chinese (n = 71), European (n = 416), and Hispanic/Latino (n = 301), as well as in all populations combined. As expected, fine-mapping produced more significant protein prediction models, especially in African ancestries populations, potentially increasing opportunity for discovery. When we tested our TOPMed MESA models in the independent European INTERVAL study, fine-mapping improved cross-ancestries prediction for some proteins. Using GWAS summary statistics from the Population Architecture using Genomics and Epidemiology (PAGE) study, which comprises ∼50,000 Hispanic/Latinos, African Americans, Asians, Native Hawaiians, and Native Americans, we applied S-PrediXcan to perform PWAS for 28 complex traits. The most protein-trait associations were discovered, colocalized, and replicated in large independent GWAS using proteome prediction model training populations with similar ancestries to PAGE. At current training population sample sizes, performance between baseline and fine-mapped protein prediction models in PWAS was similar, highlighting the utility of elastic net. Our predictive models in diverse populations are publicly available for use in proteome mapping methods at https://doi.org/10.5281/zenodo.4837327

Improved functionalization of oleic acid-coated iron oxide nanoparticles for biomedical applications

Superparamagnetic iron oxide nanoparticles can providemultiple benefits for biomedical applications in aqueous environments such asmagnetic separation or magnetic resonance imaging. To increase the colloidal stability and allow subsequent reactions, the introduction of hydrophilic functional groups onto the particles’ surface is essential. During this process, the original coating is exchanged by preferably covalently bonded ligands such as trialkoxysilanes. The duration of the silane exchange reaction, which commonly takes more than 24 h, is an important drawback for this approach. In this paper, we present a novel method, which introduces ultrasonication as an energy source to dramatically accelerate this process, resulting in high-quality waterdispersible nanoparticles around 10 nmin size. To prove the generic character, different functional groups were introduced on the surface including polyethylene glycol chains, carboxylic acid, amine, and thiol groups. Their colloidal stability in various aqueous buffer solutions as well as human plasma and serum was investigated to allow implementation in biomedical and sensing applications.status: publishe

In search of value-for-money in collective bargaining: an analytic-interactive mediation process

In this paper we introduce an analytic-interactive mediation approach to facilitate conflict resolution in collective bargaining. Based on field observations of labor-management negotiations in the German railway industry, we develop an approach which combines human mediation with IT-based contract modeling. The system addresses two shortcomings of existing negotiation support systems (NSS) for collective bargaining: first, limited information exchanges to computer-based channels and, second, a lack of frameworks, which reflect existing cognitive schemes of labor-management negotiators beyond standard utility vs. utility approaches. The negotiation modeling approach of the system introduced in this paper rests on the value-for-money principle, analyzing contract options based on costs for the management and benefit to the unions. We use this principle in order to design a comprehensible, and thereby applicable negotiation support system. The approach helps to identify concession exchanges across contract options that result either in small cost increases for management and large benefit gains to the union, or large cost savings and few benefit losses. We apply the system to a case study to show that pareto-improvements can serve to increase the settlement probability and the quality of the final contract. The system is designed for negotiations nearing deadlock