01810nas a2200241   4500008004100000022001400041245010400055210006900159260004200228300001000270490000700280520107100287653001501358653002101373653002301394653001501417653002101432100001801453700002101471700002601492700002001518856003001538       2021                        eng d  a1927-032100aSimulating a Biorefinery Ecosystem to Manage and Motivate Sustainable Regional Nutrient Circulation0 aSimulating a Biorefinery Ecosystem to Manage and Motivate Sustai  aOttawabTalent First Networkc02/2021  a33-430 v113 aCreating an ecologically sustainable circulation of nutrients requires local solutions with commitment from all participating parties. Due to vast differences between various regions, it is very complicated, if not impossible, to create fair, simple, and applicable legislation that can consider all of these differences in a meaningful way. Thus, there is a need for clear and easy ways of developing sustainable and viable solutions locally, as well as communicating them with local community and all the way up to the supervising governmental representatives. To meet this need, we developed a simulation tool that allows the user to explore the effectiveness and impact of a local biorefinery in waste management. As an iterative model based on state machine agents, it can easily be modified for a multitude of scenarios with changes taking place over time, while considering the viewing points of all involved. In this article, we report the first version of this tool and demonstrate its usefulness in estimating suitable biogas reactor size in a biorefinery.10aBioreactor10acircular economy10anutrient recycling10asimulation10awaste management1 aKoskela, Olli1 aDempers, Clemens1 aKymäläinen, Maritta1 aNummela, Jarkko  utimreview.ca/article/142101953nas a2200217   4500008004100000022001400041245012000055210006900175260004200244300000900286490000700295520126700302100002001569700001901589700002101608700001801629700002101647700001801668700001901686856003001705       2021                        eng d  a1927-032100aA Year Acquiring and Publishing Drone Aerial Images in Research on Agriculture, Forestry, and Private Urban Gardens0 aYear Acquiring and Publishing Drone Aerial Images in Research on  aOttawabTalent First Networkc02/2021  a5-160 v113 aDrone imaging has been shown to have increasing value in monitoring and analysing different kinds of processes related to agriculture and forestry. In long-term monitoring and observation tasks, huge amounts of image data are produced and stored. Environmental drone image datasets may have value beyond the studies that produced the data. A collection of image datasets from multiple data producers can, for example, provide more diverse training input for a machine learning model for vegetation classification, compared with a single dataset limited in time and location. To ensure reproducible research, research data such as image datasets should be published in usable and undegraded form, with sufficient metadata. Timely storage in a stable research data repository is recommended, to avoid loss of data. This work presents research datasets of 2020 drone images acquired from agricultural and forestry research sites of Häme University of Applied Sciences, and from Hämeenlinna urban areas. Those images that do not contain personal data are made freely available under a Creative Commons Attribution license. For images containing personal data, such as images of private homes, privacy preserving forms of data sharing may be possible in the future.1 aNiemitalo, Olli1 aKoskinen, Eero1 aHyväluoma, Jari1 aLientola, Esa1 aLindberg, Henrik1 aKoskela, Olli1 aKunttu, Iivari  utimreview.ca/article/1418