| 1. |
- van Oosterom, Peter, et al.
(författare)
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Preface: Spatial data for design
- 2023
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Ingår i: 26th AGILE Conference on Geographic Information Science : Spatial data for design - Spatial data for design. ; 4
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
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| 2. |
- DeJongh, J, et al.
(författare)
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Estimation of systemic toxicity of acrylamide by integration of in vitro toxicity data with kinetic simulations.
- 1999
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Ingår i: Toxicology and Applied Pharmacology. - : Elsevier BV. - 0041-008X .- 1096-0333. ; 158:3, s. 261-268
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Tidskriftsartikel (refereegranskat)abstract
- Neurodegenerative properties of acrylamide were studied in vitro by exposure of differentiated SH-SY5Y human neuroblastoma cells for 72 h. The number of neurites per cell and the total cellular protein content were determined every 24 h throughout the exposure and the subsequent 96-h recovery period. Using kinetic data on the metabolism of acrylamide in rat, a biokinetic model was constructed in which the in vitro toxicity data were integrated. Using this model, we estimated the acute and subchronic toxicity of acrylamide for the rat in vivo. These estimations were compared to experimentally derived lowest observed effect doses (LOEDs) for daily intraperitoneal exposure (1, 10, 30, and 90 days) to acrylamide. The estimated LOEDs differed maximally twofold from the experimental LOEDs, and the nonlinear response to acrylamide exposure over time was simulated correctly. It is concluded that the integration of the present in vitro toxicity data with kinetic data gives adequate estimates of acute and subchronic neurotoxicity resulting from acrylamide exposure.
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| 3. |
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| 4. |
- Ploeger, A, et al.
(författare)
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Evolutionary Psychology as a Metatheory for the Social Sciences: How to Gather Interdisciplinary Evidence for a Psychological Adaptation
- 2015
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Ingår i: REVIEW OF GENERAL PSYCHOLOGY. - : SAGE Publications. - 1089-2680 .- 1939-1552. ; 19:3, s. 381-392
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Evolutionary psychology has been proposed as a new metatheory for the social sciences ( Buss, 1995 ). Evolutionary psychology is an approach that emphasizes the evolutionary background of psychological phenomena (e.g., cognition, motivation, perception), with the expectation that knowledge about this background enhances our understanding of the working of the present human mind. This proposal has met with both enthusiasm and criticism. An important criticism is that it is hard, if possible at all, to find empirical evidence for a hypothesized psychological adaptation. This criticism has been addressed with the proposal to build a nomological network of evidence around a hypothesized psychological adaptation ( Schmitt & Pilcher, 2004 ). In this article, we show that it is possible to use this nomological network of evidence to support the hypothesis that face recognition is an adaptation. We reviewed the literature on face recognition from different disciplines (psychology, medicine, neuroscience, genetics, primatology, and anthropology) and conclude that there is an extensive network of evidence for the proposed hypothesis. We argue that building a nomological network of evidence is a promising way to address several criticisms of evolutionary psychology, and that such a network can serve as a metatheoretical framework for the social sciences.
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| 5. |
- Ren, Qilin, et al.
(författare)
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Modeling the choice of shared micro-mobility services using XGBoost machine learning
- 2023
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Ingår i: 26th AGILE Conference on Geographic Information Science : Spatial data for design - Spatial data for design. ; 4:4
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Bokkapitel (refereegranskat)abstract
- In recent years, shared micro-mobility services (e.g., bikes, e-bikes, and e-scooters) have been popularized at a rapid pace worldwide, which provide more choices for people’s short and medium-distance travel. Accurately modeling the choice of these shared micro-mobility services is important for their regulation and management. However, little attention has been paid to modeling their choice, especially with machine learning. In this paper, we explore the potential of the XGBoost model to model the three types of shared micro-mobility services, including docked bike, docked e-bike, and dockless e-scooter, in Zurich, Switzerland. The model achieves an accuracy of 72.6%. Moreover, the permutation feature importance is implemented to interpret the model prediction. It is found that trip duration, trip distance, and difference in elevation present higher feature importance in the prediction. The findings are beneficial for urban planners and operators to further improve the shared micro-mobility services toward sustainable urban mobility.
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