TY - CHAP A1 - Gonnermann, Jana A1 - Brandenburger, Bonny A1 - Vladova, Gergana A1 - Gronau, Norbert ED - Bui, Tung X. T1 - To what extent can individualisation in terms of different types of mode improve learning outcomes and learner satisfaction? BT - a pre-study T2 - Proceedings of the 56th Annual Hawaii International Conference on System Sciences January 3-6, 2023 N2 - With the latest technological developments and associated new possibilities in teaching, the personalisation of learning is gaining more and more importance. It assumes that individual learning experiences and results could generally be improved when personal learning preferences are considered. To do justice to the complexity of the personalisation possibilities of teaching and learning processes, we illustrate the components of learning and teaching in the digital environment and their interdependencies in an initial model. Furthermore, in a pre-study, we investigate the relationships between the learner's ability to (digital) self-organise, the learner’s prior- knowledge learning in different variants of mode and learning outcomes as one part of this model. With this pre-study, we are taking the first step towards a holistic model of teaching and learning in digital environments. KW - advances in teaching and learning technologies KW - digital learning KW - digital teaching KW - experimental design KW - personalised learning KW - teaching and learning model Y1 - 2023 SN - 978-0-9981331-6-4 SP - 123 EP - 132 PB - Department of IT Management Shidler College of Business University of Hawaii CY - Honolulu, HI ER - TY - JOUR A1 - Wang, Hao A1 - Wang, Xue-jiang A1 - Wang, Wei-shi A1 - Yan, Xiang-bo A1 - Xia, Peng A1 - Chen, Jie A1 - Zhao, Jian-fu T1 - Modeling and optimization of struvite recovery from wastewater and reusing for heavy metals immobilization in contaminated soil JF - Journal of chemical technology & biotechnology N2 - BACKROUND: Few studies have been carried out to connect nutrients recovery from wastewater and heavy metals immobilization in contaminated soil. To achieve the goal, ammonia nitrogen (AN) and phosphorus (P) were recovered from rare-earth wastewater by using the formation of struvite, which was used as the amendment with plant ash for copper, lead and chromium immobilization. RESULTS: AN removal efficiency and residual P reached 95.32 +/- 0.73% and 6.14 +/- 1.72mgL(-1) under optimal conditions: pH= 9.0, n(Mg): n(N): n(P)= 1.2: 1: 1.1, which were obtained using response surface methodology (RSM). The minimum available concentrations of Cu, Pb and Cr (CPC) separately reduced to 320.82 mg kg(-1), 190.77 mg kg(-1) and 121.46 mg kg(-1) with increasing immobilization time at the mass ratio of phosphate precipitate (PP)/plant ash (PA) of 1: 3. Humic acid (HA) and fulvic acid (FA) were beneficial to immobilize Cu, both of which showed no effect or even a negative effect on Pb and Cr immobilization. KW - precipitation KW - experimental design KW - immobilization KW - heavy metals KW - environmental remediation Y1 - 2016 U6 - https://doi.org/10.1002/jctb.4931 SN - 0268-2575 SN - 1097-4660 VL - 91 SP - 3045 EP - 3052 PB - Wiley-Blackwell CY - Hoboken ER - TY - JOUR A1 - Kraus, Sara Milena A1 - Mathew-Stephen, Mariet A1 - Schapranow, Matthieu-Patrick T1 - Eatomics BT - Shiny exploration of quantitative proteomics data JF - Journal of proteome research N2 - Quantitative proteomics data are becoming increasingly more available, and as a consequence are being analyzed and interpreted by a larger group of users. However, many of these users have less programming experience. Furthermore, experimental designs and setups are getting more complicated, especially when tissue biopsies are analyzed. Luckily, the proteomics community has already established some best practices on how to conduct quality control, differential abundance analysis and enrichment analysis. However, an easy-to-use application that wraps together all steps for the exploration and flexible analysis of quantitative proteomics data is not yet available. For Eatomics, we utilize the R Shiny framework to implement carefully chosen parts of established analysis workflows to (i) make them accessible in a user-friendly way, (ii) add a multitude of interactive exploration possibilities, and (iii) develop a unique experimental design setup module, which interactively translates a given research hypothesis into a differential abundance and enrichment analysis formula. In this, we aim to fulfill the needs of a growing group of inexperienced quantitative proteomics data analysts. Eatomics may be tested with demo data directly online via https://we.analyzegenomes.com/now/eatomics/or with the user's own data by installation from the Github repository at https://github.com/Millchmaedchen/Eatomics. KW - R Shiny KW - application KW - label-free KW - proteomics KW - analysis KW - differential KW - abundance KW - experimental design Y1 - 2021 U6 - https://doi.org/10.1021/acs.jproteome.0c00398 SN - 1535-3893 SN - 1535-3907 VL - 20 IS - 1 SP - 1070 EP - 1078 PB - American Chemical Society CY - Washington ER - TY - JOUR A1 - Keser, Claudia A1 - Kliemt, Hartmut A1 - Späth, Maximilian T1 - Charitable giving BT - the role of framing and information JF - PLoS ONE N2 - We investigate how different levels of information influence the allocation decisions of donors who are entitled to freely distribute a fixed monetary endowment between themselves and a charitable organization in both giving and taking frames. Participants donate significantly higher amounts, when the decision is described as taking rather than giving. This framing effect becomes smaller if more information about the charity is provided. KW - experimental economics KW - dictator game KW - experimental design KW - labor economics KW - welfare economics KW - language KW - prosocial behavior KW - university laboratories Y1 - 2023 U6 - https://doi.org/10.1371/journal.pone.0288400 SN - 1932-6203 VL - 18 IS - 7 PB - Public Library of Science (PLoS) CY - San Francisco, California ER -