Kokstern3797

Understanding the activities and preferences of visitors is crucial for managing protected areas and planning conservation strategies. Conservation culturomics promotes the use of user-generated online content in conservation science. Geotagged social media content is a unique source of in situ information on human presence and activities in nature. Photographs posted on social media platforms are a promising source of information, but analyzing large volumes of photographs manually remains laborious. We examined the application of state-of-the-art computer-vision methods to studying human-nature interactions. We used semantic clustering, scene classification, and object detection to automatically analyze photographs taken in Finnish national parks by domestic and international visitors. Our results showed that human-nature interactions can be extracted from user-generated photographs with computer vision. Tideglusib clinical trial The different methods complemented each other by revealing broad visual themes related to level of the data set, landscape photogeneity, and human activities. Geotagged photographs revealed distinct regional profiles for national parks (e.g., preferences in landscapes and activities), which are potentially useful in park management. Photographic content differed between domestic and international visitors, which indicates differences in activities and preferences. Information extracted automatically from photographs can help identify preferences among diverse visitor groups, which can be used to create profiles of national parks for conservation marketing and to support conservation strategies that rely on public acceptance. The application of computer-vision methods to automatic content analysis of photographs should be explored further in conservation culturomics, particularly in combination with rich metadata available on social media platforms.Per- and polyfluoroalkyl substances (PFAS) have been around for decades and have been the subject of laboratory and field research studies for nearly as long. Although attention to PFAS has grown in recent years, many unanswered questions remain. Accordingly, the number of research projects designed to improve our understanding of PFAS toxicity, bioaccumulation, and biomagnification, and to improve our ability to predict the interactions of PFAS mixtures, is also increasing. The growing number of ongoing and future research projects focusing on these chemicals will benefit from lessons learned in previous studies. This perspectives article discusses available approaches to mixture risk assessment with specific focus on application to PFAS mixtures. We discuss ongoing research as well as lessons learned from approaches to handling mixtures of other groups of chemicals. Many of these approaches require some detailed understanding of a manageable number of representative chemicals, yet only limited toxicologicalmmunity structure studies, may be needed to fully understand potential impacts of mixtures. Integr Environ Assess Manag 2021;17697-704. © 2021 SETAC.

CEST MRI omega plot quantifies the labile proton fraction ratio (f

) and exchange rate (k

), yet it assumes long RF saturation time (Ts) and relaxation delay (Td). Our study aimed to test if a quasi-steady-state (QUASS) CEST analysis that accounts for the effect of finite Ts and Td could improve the accuracy of CEST MRI quantification.

We modeled the MRI signal evolution using a typical CEST EPI sequence. The signal relaxes toward its thermal equilibrium following the bulk water relaxation rate during Td, and then toward its CEST steady state following the spin-lock relaxation rate during Ts from which the QUASS CEST effect is derived. Both f

and k

were solved from simulated conventional apparent CEST and QUASS CEST MRI. We also performed MRI experiments from a Cr-gel phantom under serially varied Ts and Td times from 1.5 to 7.5 s.

Simulation showed that, although k

could be slightly overestimated (3%-15%) for the range of Ts and Td, f

could be substantially underestimated by as much as 67%. In contrast, the QUASS solution provided accurate k

and f

determination within 2%. The CEST MRI experiments confirmed that the QUASS solution enabled robust quantification of k

and f

, superior over the omega plot analysis based on the conventional apparent CEST MRI measurements.

The QUASS CEST MRI algorithm corrects the effect of finite Ts and Td times on CEST measurements, thereby allowing robust and accurate CEST quantification.

The QUASS CEST MRI algorithm corrects the effect of finite Ts and Td times on CEST measurements, thereby allowing robust and accurate CEST quantification.The recent growth of online big data offers opportunities for rapid and inexpensive measurement of public interest. Conservation culturomics is an emerging research area that uses online data to study human-nature relationships for conservation. Methods for conservation culturomics, though promising, are still being developed and refined. We considered the potential of Wikipedia, the online encyclopedia, as a resource for conservation culturomics and outlined methods for using Wikipedia data in conservation. Wikipedia's large size, widespread use, underlying data structure, and open access to both its content and usage analytics make it well suited to conservation culturomics research. Limitations of Wikipedia data include the lack of location information associated with some metadata and limited information on the motivations of many users. Seven methodological steps to consider when using Wikipedia data in conservation include metadata selection, temporality, taxonomy, language representation, Wikipedia geography, physical and biological geography, and comparative metrics. Each of these methodological decisions can affect measures of online interest. As a case study, we explored these themes by analyzing 757 million Wikipedia page views associated with the Wikipedia pages for 10,099 species of birds across 251 Wikipedia language editions. We found that Wikipedia data have the potential to generate insight for conservation and are particularly useful for quantifying patterns of public interest at large scales.