What will a shopping street look like in 2025, when online shopping continues to show double-digit growth? And what will 3D printing do to factories and logistic companies, when we can ‘print’ more and more products at home or around the corner?The digital economy is one of the most pervasive game changers in cities. It creates and destroys, and affects the way cities function in many ways. But what is exactly the digital economy about? How big is it? Which types of transformation is it provoking in urban economies? And, importantly, what can local governments do to cope with the digital transition and foster sustainable urban development?
MULTIFILE
Concerns have been raised over the increased prominence ofgenerative AI in art. Some fear that generative models could replace theviability for humans to create art and oppose developers training generative models on media without the artist's permission. Proponents of AI art point to the potential increase in accessibility. Is there an approach to address the concerns artists raise while still utilizing the potential these models bring? Current models often aim for autonomous music generation. This, however, makes the model a black box that users can't interact with. By utilizing an AI pipeline combining symbolic music generation and a proposed sample creation system trained on Creative Commons data, a musical looping application has been created to provide non-expert music users with a way to start making their own music. The first results show that it assists users in creating musical loops and shows promise for future research into human-AI interaction in art.
Despite growing popular interest for the mental health of electronic music artists, scientific research addressing this topic has remained largely absent. As such, the aim of the current study was to examine the mental health of electronic music artists, as well as a number of determinants. Using a cross-sectional quantitative design, a total of 163 electronic music artists participated in this study. In line with the two-continua model of mental health, both symptoms of depression/anxiety and well-being were adopted as indicators for mental health. Furthermore, standardized measures were used to assess potential determinants of mental health, including sleep disturbance, music performance anxiety, alcohol abuse, drug abuse, occupational stress, resilience, and social support. Results highlighted that around 30% of participants experienced symptoms of depression/anxiety. Nevertheless, the majority of these participants still demonstrated at least moderate levels of functioning and well-being. Sleep disturbance formed a significant predictor for both symptoms of depression/anxiety and well-being. Furthermore, resilience and social support were significant predictors for well-being. The results provide a first glimpse into the mental health challenges experienced by electronic music artists and support the need for increased research as well as applied initiatives directed at safeguarding their mental health.
