Hedonic (happiness) and eudaimonic (meaning in life) well-being are negatively related to depressive symptoms. Genetic variants play a role in this association, reflected in substantial genetic correlations. We investigated the overlap and differences between well-being and depressive symptoms, using results of Genome-Wide Association studies (GWAS) in UK Biobank. Subtracting GWAS summary statistics of depressive symptoms from those of happiness and meaning in life, we obtained GWASs of respectively “pure” happiness (neffective = 216,497) and “pure” meaning (neffective = 102,300). For both, we identified one genome-wide significant SNP (rs1078141 and rs79520962, respectively). After subtraction, SNP heritability reduced from 6.3% to 3.3% for pure happiness and from 6.2% to 4.2% for pure meaning. The genetic correlation between the well-being measures reduced from 0.78 to 0.65. Pure happiness and pure meaning became genetically unrelated to traits strongly associated with depressive symptoms, including loneliness, and psychiatric disorders. For other traits, including ADHD, educational attainment, and smoking, the genetic correlations of well-being versus pure well-being changed substantially. GWAS-by-subtraction allowed us to investigate the genetic variance of well-being unrelated to depressive symptoms. Genetic correlations with different traits led to new insights about this unique part of well-being. Our results can be used as a starting point to test causal relationships with other variables, and design future well-being interventions.
MULTIFILE
While consumers have become increasingly aware of the need for sustainability in fashion, many do not translate their intention to purchase sustainable fashion into actual behavior. Insights can be gained from those who have successfully transitioned from intention to behavior (i.e., experienced sustainable fashion consumers). Despite a substantial body of literature exploring predictors of sustainable fashion purchasing, a comprehensive view on how predictors of sustainable fashion purchasing vary between consumers with and without sustainable fashion experience is lacking. This paper reports a systematic literature review, analyzing 100 empirical articles on predictors of sustainable fashion purchasing among consumer samples with and without purchasing experience, identified from the Web of Science and Scopus databases.
MULTIFILE
Emotions embody the value in tourism experiences and drive essential outcomes such as intent to recommend. Current models do not explain how the ebb and flow of emotional arousal during an experience relate to outcomes, however. We analyzed 15 participants’ experiences at the Vincentre museum and guided village tour in Nuenen, the Netherlands. This Vincent van Gogh-themed experience led to a wide range of intent to recommend and emotional arousal, measured as continuous phasic skin conductance, across participants and exhibits. Mixed-effects analyses modeled emotional arousal as a function of proximity to exhibits and intent to recommend. Experiences with the best outcomes featured moments of both high and low emotional arousal, not one continuous “high,” with more emotion during the middle of the experience. Tourist experience models should account for a complex relationship between emotions experienced and outcomes such as intent to recommend. Simply put, more emotion is not always better.
About half of the e-waste generated in The Netherlands is properly documented and collected (184kT in 2018). The amount of PCBs in this waste is projected to be about 7kT in 2018 with a growth rate of 3-4%. Studies indicate that a third of the weight of a PCB is made or recoverable and critical metals which we need as resources for the various societal challenges facing us in the future. Recycling a waste PCB today means first shredding it and then processing it for material recovery mostly via non-selective pyrometallurgical methods. Sorting the PCBs in quality grades (wastebins) before shredding would however lead to more flexibility in selecting when and which recovery metallurgy is to be used. The yield and diversity of the recovered metals increases as a result, especially when high-grade recycling techniques are used. Unfortunately, the sorting of waste PCBs is not easily automated as an experienced operator eye is needed to classify the very inhomogeneous waste-PCB stream in wastebins. In this project, a knowledge institution partners with an e-waste processor, a high-grade recycling technology startup and a developer of waste sorting systems to investigate the efficiency of methods for sensory sorting of waste PCBs. The knowledge gained in this project will lead towards a waste PCB sorting demonstrator as a follow-up project.
