Detection and identification of body fluids are crucial aspects of forensic investigations, aiding in crime scene reconstructions and providing important leads. Although many methods have been developed for these purposes, no method is currently in use in the forensic field that allows rapid, non-contact detection and identification of vaginal fluids directly at the crime scene. The development of such technique is mainly challenged by the complex chemistry of the constituents, which can differ between donors and exhibits changes based on woman’s menstrual cycle. The use of fluorescence spectroscopy has shown promise in this area for other biological fluids. Therefore, the aim of this study was to identify specific fluorescent signatures of vaginal fluid with fluorescence spectroscopy to allow on-site identification. Additionally, the fluorescent properties were monitored over time to gain insight in the temporal changes of the fluorescent spectra of vaginal fluid. The samples were excited at wavelengths ranging from 200 to 600 nm and the induced fluorescence emission was measured from 220 to 700 nm. Excitation and emission maps (EEMs) were constructed for eight donors at seven time points after donation. Four distinctive fluorescence peaks could be identified in the EEMs, indicating the presence of proteins, fluorescent oxidation products (FOX), and an unidentified component as the dominant contributors to the fluorescence. To further asses the fluorescence characteristics of vaginal fluid, the fluorescent signatures of protein and FOX were used to monitor protein and lipid oxidation reactions over time. The results of this study provide insights into the intrinsic fluorescent properties of vaginal fluid over time which could be used for the development of a detection and identification method for vaginal fluids. Furthermore, the observed changes in fluorescence signatures over time could be utilized to establish an accurate ageing model.
This paper presents the latest version of the Machinations framework. This framework uses diagrams to represent the flow of tangible and abstract resources through a game. This flow represents the mechanics that make up a game’s interbal economy and has a large impact on the emergent gameplay of most simulation games, strategy games and board games. This paper shows how Machinations diagrams can be used simulate and balance games before they are built.
Regional sustainability networks in the Netherlands are rooted in regionalculture and have an emphasis on social learning and effective collaboration between multiple actors. The national ‘Duurzaam Door’ (Moving Forward Sustainably) Policy Programme regards these networks as generative governance arrangements where new knowledge, actions and relations can co-evolve together with new insights in governance and learning within sustainability transitions. In order to understand the dynamics of the learning in these networks we have monitored emergent properties of social learning between 2014 and 2016. Our focus is particularly on the interrelated role of trust, commitment, reframing and reflexivity. Our aim is to better understand the role and the dynamics of these emergent properties and to see which actors and roles can foster the effectiveness of social learning in regional transitions towards more sustainable ways of living. We used a retrospective analysis with Reflexive Monitoring in Action (RMA), which we combined with the Most Significant Change approach. We found that reflexivity in particularis a critical property at moments that can make or break the process.
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