Pervasive learning analytics for fostering learners' self-regulation

Today's tertiary STEM (Science, Technology, Engineering and Mathematics) education in Europe poses problems to both teachers and students. With growing enrolment numbers, and numbers of teaching staff that are outmatched by this growth, student-teacher contact becomes more and more difficult to provide. Therefore, students are required to quickly adopt self-regulated and autonomous learning styles when entering European universities. Furthermore, teachers are required to divide their attention between large numbers of students. As a consequence, classical teaching formats of STEM education which often encompass experimentation or active exploration, become harder to implement. Educational software holds the promise of easing these problems, or, if not fully solving, at least of making them less acute: Learning Analytics generated by such software can foster self-regulation by providing students with both formative feedback and assessments. Educational software, in form of collaborative social media, makes it easier for teachers to collaborate, allows to reduce their workload and enables learning and teaching formats otherwise infeasible in large classes. The contribution of this thesis is threefold: Firstly, it reports on a social medium for tertiary STEM education called "Backstage2 / Projects" aimed specifically at these points: Improving learners' self-regulation by providing pervasive Learning Analytics, fostering teacher collaboration so as to reduce their workload, and providing means to deploy a variety of classical and novel learning and teaching formats in large classes. Secondly, it reports on several case studies conducted with that medium which point at the effectiveness of the medium and its provided Learning Analytics to increase learners' self-regulation, reduce teachers' workload, and improve how students learn. Thirdly, this thesis reports on findings from Learning Analytics which could be used in the future in designing further teaching and learning formats or case studies, yielding a rich perspective for future research and indications for improving tertiary STEM education

Climate resilience for a neighborhood without privilege: East Boston

This architecture thesis is about climate change and unprivileged populations – sea-level rise in particular, and the neighborhood of East Boston. Across recorded human history, the burdens of climate stress have fallen disproportionately on marginal populations, and today is no different. We don’t have to travel to a South Pacific island to see the risk posed by sea-level rise – that risk can be found right here along the New England coastline. Neighborhoods with a minimum of privilege face challenges to their existence – and those residents want to stay in their homes and preserve their communities just like anybody else. This project examines a series of tactical design interventions to help the community of East Boston stay in place but adapt to a future that includes periodic and sustained flooding. How will homeowners respond, individually and collectively? Substantial public assets – health centers, boys-and-girls clubs, schools and churches – knit together the community. How can we modify those structures in place to be resilient toward rising sea levels? With a grounding in prior architectural responses to traumatic changes in the built environment (sea-level rise among them), we propose specific steps for sites in the neighborhoods of Maverick Square and Jeffries Point

Parabolic opers and differential operators

Parabolic SL(r,C)-opers were defined and investigated in [BDP] in the set-up of vector bundles on curves with a parabolic structure over a divisor. Here we introduce and study holomorphic differential operators between parabolic vector bundles over curves. We consider the parabolic SL(r,C)-opers on a Riemann surface X with given singular divisor S and with fixed parabolic weights satisfying the condition that all parabolic weights at any point $x_i$ in S are integral multiples of $\frac{1}{2N_i+1}$, where $N_i > 1$ are fixed integers. We prove that this space of opers is canonically identified with the affine space of holomorphic differential operators of order r between two natural parabolic line bundles on X (depending only on the divisor S and the weights $N_i$) satisfying the conditions that the principal symbol of the differential operators is the constant function 1 and the sub-principal symbol vanishes identically. The vanishing of the sub-principal symbol ensures that the logarithmic connection on the rank r bundle is actually a logarithmic SL(r, C)-connection.Comment: Final version accepted for publication in Journal of Geometry and Physic

Design Of A Material Flow Method And Technology Procedure For Battery Cell Production In Mini-Environments

Due to the rising interest in electric vehicles, the demand for more efficient battery cells is increasing rapidly and immense production capacity expansions are announced in the next decade. Manufacturing of lithium-ion battery cells is complex and highly influenced by the environmental product conditions. Nearly along the hole value chain, the production processes take place in so-called clean and dry rooms to strictly control humidity and particular contamination. Cleanliness can be ensured with appropriate air management systems, while dry air handling is technically and energetically much more complex. To counteract this, the mini-environment approach reduces the amount of air, as the system is enclosed airtight in a process- and product-oriented manner. Mini-environments offer the possibility of replacing conventional clean and dry rooms through energy and cost savings, improved product quality and increased operator safety. However, to rollout the mini-environment approach in battery cell production facilities, production methods and technologies must be developed and researched. Next to the machine level, especially the material flow level must be addressed and is key for the holistic integration of the mini-environment approach in production facilities. Moreover, due to cross-machine movements while maintaining constant and stable atmosphere conditions, there are currently no logistics or airlock solutions tailored for battery cell production. This paper provides a method named MiniMaFlow including systematically developed solutions to enable modular and rigid material flow in mini-environments. The method is conducted to fulfill the cleanliness and humidity requirements with focus on innovation, costs, and sustainability. A first modular prototype has been designed to achieve detailed level for production research. With this, a holistic analysis and evaluation is conducted compared to the state of the art. In conclusion, a validated transferable potential heat-map and a use-case-specific quantitative evaluation for technology-implementation are shown as a result

Time-averaged order parameter restraints in molecular dynamics simulations

A method is described that allows experimental $$S^2$$ S 2 order parameters to be enforced as a time-averaged quantity in molecular dynamics simulations. The two parameters that characterize time-averaged restraining, the memory relaxation time and the weight of the restraining potential energy term in the potential energy function used in the simulation, are systematically investigated based on two model systems, a vector with one end restrained in space and a pentapeptide. For the latter it is shown that the backbone N-H order parameter of individual residues can be enforced such that the spatial fluctuations of quantities depending on atomic coordinates are not significantly perturbed. The applicability to realistic systems is illustrated for the B3 domain of protein G in aqueous solution

Surface ocean iron fertilization: the role of subduction zone and hotspot volcanic ash and fluxes into the Pacific Ocean

Surface ocean iron (Fe) fertilization can affect the marine primary productivity (MPP), thereby impacting on CO2 exchanges at the atmosphere-ocean interface and eventually on climate. Mineral (aeolian or desert) dust is known to be a major atmospheric source for the surface ocean biogeochemical iron cycle, but the significance of volcanic ash is poorly constrained. We present the results of geochemical experiments aimed at determining the rapid release of Fe upon contact of pristine volcanic ash with seawater, mimicking their dry deposition into the surface ocean. Our data show that volcanic ash from both subduction zone and hot spot volcanoes (n = 44 samples) rapidly mobilized significant amounts of soluble Fe into seawater (35–340 nmol/g ash), with a suggested global mean of 200 ± 50 nmol Fe/g ash. These values are comparable to the range for desert dust in experiments at seawater pH (10–125 nmol Fe/g dust) presented in the literature (Guieu et al., 1996; Spokes et al., 1996). Combining our new Fe release data with the calculated ash flux from a selected major eruption into the ocean as a case study demonstrates that single volcanic eruptions have the potential to significantly increase the surface ocean Fe concentration within an ash fallout area. We also constrain the long-term (millennial-scale) airborne volcanic ash and mineral dust Fe flux into the Pacific Ocean by merging the Fe release data with geological flux estimates. These show that the input of volcanic ash into the Pacific Ocean (128–221 × 1015 g/ka) is within the same order of magnitude as the mineral dust input (39–519 × 1015 g/ka) (Mahowald et al., 2005). From the similarity in both Fe release and particle flux follows that the flux of soluble Fe related to the dry deposition of volcanic ash (3–75 × 109 mol/ka) is comparable to that of mineral dust (1–65 × 109 mol/ka). Our study therefore suggests that airborne volcanic ash is an important but hitherto underestimated atmospheric source for the Pacific surface ocean biogeochemical iron cycle