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Colorful photothermal photonic crystal cotton fabric based on melanin-like polycaffeic acid nanoparticles
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Work it baby! A survey study to investigate the role of underaged children and privacy management strategies within parent influencer content
No full textNowadays, parents are increasingly drawn to establish a successful influencer status on social media. Being a parent influencer offers an alluring work environment, allowing them to combine devotion to their children and generating a considerable income. However, both scholars and policymakers raise significant concerns regarding the orchestrated and monetized nature of influencer sharenting, which involves sharing children's personal information online. The present study, which surveyed 89 parent influencers from Belgium and The Netherlands, shows that children are omnipresent in their parents' influencer content. The findings do not only uncover the underlying motivations driving influencer sharenting, but also reveal a low sharenting risk awareness. Building on parent influencers' safe sharenting strategies, this study identifies three parent influencer types: reckless, safe, and authoritarian safe sharenters. This classification contributes to a better understanding of the heterogeneity of the parent influencer landscape and will foster the development of protective measures in favor of children's wellbeing.Nowadays, parents are increasingly drawn to establish a successful influencer status on social media. Being a parent influencer offers an alluring work environment, allowing them to combine devotion to their children and generating a considerable income. However, both scholars and policymakers raise significant concerns regarding the orchestrated and monetized nature of influencer sharenting, which involves sharing children's personal information online. The present study, which surveyed 89 parent influencers from Belgium and The Netherlands, shows that children are omnipresent in their parents' influencer content. The findings do not only uncover the underlying motivations driving influencer sharenting, but also reveal a low sharenting risk awareness. Building on parent influencers' safe sharenting strategies, this study identifies three parent influencer types: reckless, safe, and authoritarian safe sharenters. This classification contributes to a better understanding of the heterogeneity of the parent influencer landscape and will foster the development of protective measures in favor of children's wellbeing.A
Geostatistical inversion of frequency-domain electromagnetic data for near surface modelling
No full textThe detailed characterization of near-surface deposits is important for both environmental and economic reasons. These shallow subsurface systems can be very complex and heterogenous due to natural dynamics and anthropogenic interferences. Modeling techniques based exclusively on direct sampling generate limited informed three-dimensional models of the near-surface. Geophysical methods provide valuable and additional information to model the spatial distribution of the near-surface for locations where direct observations are not available. From this set of methods, frequency-domain electromagnetic induction (FDEM) has been successfully applied to image complex near-surface deposits. Yet, predicting the spatial distribution of relevant subsurface properties from geophysical data, and the integration of direct observations, is not straightforward. It requires solving a challenging geophysical inversion problem. Geostatistical modelling tools have been effectively applied to couple direct observations with geophysical data such as seismic reflection. We propose an iterative geostatistical FDEM inversion method able to integrate data from direct measurements of the near-surface with surface loop-loop FDEM measurements to simultaneously predict high-resolution models of electrical conductivity and magnetic susceptibility, and their associated uncertainty. The iterative geostatistical inversion method is based on stochastic sequential simulation and co-simulation as model perturbation and update techniques. The iterative optimization is based on the local data misfit between observed and simulated FDEM data, weighted by the sensitivity of the acquisition equipment. The proposed method is first demonstrated for a synthetic landfill data set created based on real data collected at a mine tailing disposal site in Portugal, and on a real data set collected at a site with archaeological features in Knowlton, UK. The results show the ability of the proposed method to accurately predict and characterize the spatial distribution of electrical conductivity and magnetic susceptibility down to the depth of interest while reproducing the recorded FDEM data.The detailed characterization of near-surface deposits is important for both environmental and economic reasons. These shallow subsurface systems can be very complex and heterogenous due to natural dynamics and anthropogenic interferences. Modeling techniques based exclusively on direct sampling generate limited informed three-dimensional models of the near-surface. Geophysical methods provide valuable and additional information to model the spatial distribution of the near-surface for locations where direct observations are not available. From this set of methods, frequency-domain electromagnetic induction (FDEM) has been successfully applied to image complex near-surface deposits. Yet, predicting the spatial distribution of relevant subsurface properties from geophysical data, and the integration of direct observations, is not straightforward. It requires solving a challenging geophysical inversion problem. Geostatistical modelling tools have been effectively applied to couple direct observations with geophysical data such as seismic reflection. We propose an iterative geostatistical FDEM inversion method able to integrate data from direct measurements of the near-surface with surface loop-loop FDEM measurements to simultaneously predict high-resolution models of electrical conductivity and magnetic susceptibility, and their associated uncertainty. The iterative geostatistical inversion method is based on stochastic sequential simulation and co-simulation as model perturbation and update techniques. The iterative optimization is based on the local data misfit between observed and simulated FDEM data, weighted by the sensitivity of the acquisition equipment. The proposed method is first demonstrated for a synthetic landfill data set created based on real data collected at a mine tailing disposal site in Portugal, and on a real data set collected at a site with archaeological features in Knowlton, UK. The results show the ability of the proposed method to accurately predict and characterize the spatial distribution of electrical conductivity and magnetic susceptibility down to the depth of interest while reproducing the recorded FDEM data.A
Less antipsychotics, more Quality of Life Tapering strategies for adults with intellectual disabilities and challenging behaviour
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Confidentiality, privacy, and data protection in biomedicine : international concepts and issues /
No full textIncludes bibliographical references and index.Is privacy egregiously wrong? Reflections on a concept that can make or break constitutions -- Public interest and trustworthiness : connecting the concepts through reasonable justification for (non)interference with medical confidentiality -- Big Data research : can confidentiality and fiduciary duties fill in the gaps in privacy and data protection? -- Managing access to health data for research and innovation in the EU : is a better regulatory approach possible? -- Secondary Uses of Patients' Data in the European Health Data Space : A UK-German Comparison -- The evolution of privacy governance in healthcare in post-apartheid South Africa -- Is health privacy worth the cost? -- Misuse of private information and the common law right of privacy : a new frontier in biomedicine? -- Hackers and hacked : how does the law respond to and remedy health data breaches in the Asia-Pacific? -- Challenges and opportunities for data trusts for health research -- Human organoids : things or data? -- Balancing the right to data protection with managing the care of HIV patients : experiences from the National Institute for Communicable Diseases, South Africa
Popular music and LGBTQ+ identities in the age of streaming : an explorative audience study
No full textFor this study, we conducted 24 in-depth interviews with LGBTQ+ Spotify users to understand the relations between LGBTQ+ identities, music, and music streaming. Participants displayed a wide range of meaningful music practices and views on music and identity. At the same time, the interviews showcased how the impalpable and ever-changing nature of music, new media, and identities make it difficult and often undesirable to actively dissect or define the relations between music and LGBTQ+ identities, but affectively, personally, and socially they are as meaningful and prominent as ever before.For this study, we conducted 24 in-depth interviews with LGBTQ+ Spotify users to understand the relations between LGBTQ+ identities, music, and music streaming. Participants displayed a wide range of meaningful music practices and views on music and identity. At the same time, the interviews showcased how the impalpable and ever-changing nature of music, new media, and identities make it difficult and often undesirable to actively dissect or define the relations between music and LGBTQ+ identities, but affectively, personally, and socially they are as meaningful and prominent as ever before.A
