Stress and prevalence of hearing problems in the Swedish working population

<p>Abstract</p> <p>Background</p> <p>Current human and experimental studies are indicating an association between stress and hearing problems; however potential risk factors have not been established. Hearing problems are projected to become among the top ten disabilities according to the WHO in the near future. Therefore a better understanding of the relationships between stress and hearing is warranted. Here we describe the prevalence of two common hearing problems, i.e. hearing complaints and tinnitus, in relation to different work-and health-related stressors.</p> <p>Methods</p> <p>A total of 18,734 individuals were invited to participate in the study, out of which 9,756 (52%) enrolled.</p> <p>Results</p> <p>The results demonstrate a clear and mostly linear relationship between higher prevalence of hearing problems (tinnitus or hearing loss or both) and different stressors, e.g. occupational, poorer self-rated health, long-term illness, poorer sleep quality, and higher burnout scores.</p> <p>Conclusions</p> <p>The present study unambiguously demonstrates associations between hearing problems and various stressors that have not been previously described for the auditory system. These findings will open new avenues for future investigations.</p

MLSys: The New Frontier of Machine Learning Systems

Machine learning (ML) techniques are enjoying rapidly increasing adoption. However, designing and implementing the systems that support ML models in real-world deployments remains a significant obstacle, in large part due to the radically different development and deployment profile of modern ML methods, and the range of practical concerns that come with broader adoption. We propose to foster a new systems machine learning research community at the intersection of the traditional systems and ML communities, focused on topics such as hardware systems for ML, software systems for ML, and ML optimized for metrics beyond predictive accuracy. To do this, we describe a new conference, MLSys, that explicitly targets research at the intersection of systems and machine learning with a program committee split evenly between experts in systems and ML, and an explicit focus on topics at the intersection of the two

Daily self-compassion protects Asian Americans/Canadians after experiences of COVID-19 discrimination: Implications for subjective well-being and health behaviors

Asians are not immune to racial discrimination and discrimination against Asians has heightened during the COVID-19 pandemic because they were blamed as the origin of the virus. A pre-registered 14-day diary explored if self-compassion was associated with subjective well-being and protective behaviors for Asians (U.S. & Canada) who faced COVID-19 discriminations (N = 82 & ndiaries =711). Participants reported discriminations experience for 28% (U.S.) and 25% (Canada) of their days. Daily self-compassion predicted daily subjective well-being despite COVID-19 discrimination experience. Daily self-compassion predicted increased COVID-19 protective behaviors on days Asian Americans experienced COVID-19 discrimination. Daily acceptance, but not daily reappraisal, explained the link between daily self-compassion and daily subjective well-being. These findings could not be accounted for by daily self-esteem

The Seattle report on database research

Every five years, a group of the leading database researchers meet to reflect on their community's impact on the computing industry as well as examine current research challenges

The Seattle report on database research

Every five years, a group of the leading database researchers meet to reflect on their community's impact on the computing industry as well as examine current research challenges